Instruction:
You serve as an AI task planner.
1. Your task is to create a plan to achieve a goal by converting it into a sequence of actions. Each action should follow the format "[verb] <target1> <target2>", where 'verb' represents the action, and 'target1' and 'target2' are optional arguments.
2. You must describe your plan in natural language at the beginning. After that, you should list all the actions together.
Ensure that you response can be parsed by Python json.loads.

Here is an example plan to achieve a goal for reference:
Scene_Objects:['pot', 'detergent', 'ceilingfan', 'drawing', 'knifeblock', 'floor', 'ceiling', 'bedroom', 'remote_control', 'alcohol', 'table_cloth', 'ceilinglamp', 'tvstand', 'balanceball', 'plate', 'window', 'couch', 'wall', 'nightstand', 'oven', 'powersocket', 'novel', 'check', 'television', 'curtain', 'rag', 'doorjamb', 'dresser', 'table', 'clothes_skirt']
Task:Watch TV
response:
{
    "thoughts": go to living room, sit on couch, get remote, switch on tv, watch tv,
    "actions": ['[WALK] <home_office>', '[WALK] <couch>', '[FIND] <couch>', '[SIT] <couch>', '[FIND] <remote_control>', '[GRAB] <remote_control>', '[FIND] <television>', '[SWITCHON] <television>', '[TURNTO] <television>', '[LOOKAT] <television>']
}

Input:
Scene_Objects:['fork', 'filing_cabinet', 'juice', 'freezer', 'walllamp', 'drawing', 'orchid', 'phone', 'ceiling', 'character', 'cleaning_solution', 'button', 'toaster', 'ceilinglamp', 'homework', 'oil', 'mousepad', 'pillow', 'dining_room', 'food_kiwi', 'pasta', 'oven', 'coffe_maker', 'food_food', 'television', 'rag', 'towel_rack', 'bathtub', 'instrument_guitar', 'vase']
Task:Clean
response:

Spray counter tops with all purpose cleaner. Using towel, wipe counter, removing all dirt and grime until clean.

[WALK] <dining_room>
[WALK] <cleaning_solution>
[FIND] <cleaning_solution>
[GRAB] <cleaning_solution>
[PUTOBJBACK] <cleaning_solution>
[FIND] <rag>
[GRAB] <rag>
[PUTOBJBACK] <rag>


Instruction:
You serve as an AI task planner.
1. Your task is to create a plan to achieve a goal by converting it into a sequence of actions. Each action should follow the format "[verb] <target1> <target2>", where 'verb' represents the action, and 'target1' and 'target2' are optional arguments.
2. You must describe your plan in natural language at the beginning. After that, you should list all the actions together.
Ensure that you response can be parsed by Python json.loads.

Here is an example plan to achieve a goal for reference:
Scene_Objects:['filing_cabinet', 'beer', 'freezer', 'walllamp', 'drawing', 'orchid', 'cpuscreen', 'floor', 'ceiling', 'shampoo', 'bookshelf', 'remote_control', 'button', 'ceilinglamp', 'tvstand', 'mat', 'faucet', 'foundation', 'window', 'wall', 'powersocket', 'cup', 'photoframe', 'television', 'wooden_spoon', 'curtain', 'doorjamb', 'door', 'table', 'light']
Task:Change TV channel
response:
{
    "thoughts": Walk into the Living room.  Find the television remote.  Use it to turn on the television.  Point the remote at the television. Press the channel button on the remote.,
    "actions": ['[WALK] <home_office>', '[WALK] <remote_control>', '[FIND] <remote_control>', '[FIND] <television>', '[TURNTO] <television>', '[POINTAT] <television>', '[SWITCHON] <television>', '[FIND] <button>', '[PUSH] <button>']
}

Input:
Scene_Objects:['tablelamp', 'food_salt', 'microwave', 'chair', 'blow_dryer', 'nail_polish', 'trashcan', 'dough', 'needle', 'cpuscreen', 'stamp', 'thread', 'stereo', 'floor_lamp', 'mousepad', 'form', 'pillow', 'dining_room', 'nightstand', 'oven', 'bench', 'cup', 'standingmirror', 'coffe_maker', 'food_donut', 'kettle', 'door', 'home_office', 'light', 'vase']
Task:Clean
response:

[WALK] <home_office>
[WALK] <paper_towel>
[FIND] <paper_towel>
[GRAB] <paper_towel>
[WALK] <floor_lamp>
[SWITCHOFF] <floor_lamp>
[WIPE] <floor_lamp>
[FIND] <trashcan>
[PUTBACK] <paper_towel> <trashcan>


Instruction:
You serve as an AI task planner.
1. Your task is to create a plan to achieve a goal by converting it into a sequence of actions. Each action should follow the format "[verb] <target1> <target2>", where 'verb' represents the action, and 'target1' and 'target2' are optional arguments.
2. You must describe your plan in natural language at the beginning. After that, you should list all the actions together.
Ensure that you response can be parsed by Python json.loads.

Here is an example plan to achieve a goal for reference:
Scene_Objects:['sponge', 'glue', 'toilet', 'chair', 'detergent', 'dough', 'drawing', 'orchid', 'hanger', 'floor', 'ceiling', 'keyboard', 'alcohol', 'stovefan', 'ceilinglamp', 'couch', 'microphone', 'wall', 'nightstand', 'photoframe', 'coffe_maker', 'coffee_filter', 'doorjamb', 'kitchen_counter', 'hairbrush', 'cupboard', 'home_office', 'dishwasher', 'coffee', 'shoe_rack']
Task:Make coffee
response:
{
    "thoughts": Open coffee maker. Put filter in main basket, put ground coffee in filter, fill reservoir with water, turn on coffee maker.,
    "actions": ['[WALK] <dining_room>', '[WALK] <coffe_maker>', '[FIND] <coffe_maker>', '[OPEN] <coffe_maker>', '[FIND] <coffee_filter>', '[GRAB] <coffee_filter>', '[PUTBACK] <coffee_filter> <coffe_maker>', '[FIND] <coffee>', '[GRAB] <coffee>', '[PUTBACK] <coffee> <coffe_maker>']
}

Input:
Scene_Objects:['filing_cabinet', 'crayon', 'cat', 'cpuscreen', 'hanger', 'floor', 'ceiling', 'character', 'desk', 'keyboard', 'food_cake', 'computer', 'brush', 'electric_shaver', 'mousepad', 'closetdrawer', 'wall', 'wall_clock', 'powersocket', 'toy', 'food_food', 'towel_rack', 'mouse', 'dresser', 'pajamas', 'sink', 'napkin', 'light', 'colander', 'tooth_paste']
Task:Pick up toys
response:

Pickup toys from around the room. Organize toys back into their appropriate spaces on the shelves and into the toy boxes.

[WALK] <bedroom>
[WALK] <toy>
[FIND] <toy>
[GRAB] <toy>
[WALK] <filing_cabinet>
[OPEN] <filing_cabinet>
[PUTBACK] <toy> <filing_cabinet>
[CLOSE] <filing_cabinet>
[FIND] <toy>
[GRAB] <toy>
[WALK] <dresser>
[OPEN] <dresser>
[PUTBACK] <toy> <dresser>
[CLOSE] <dresser>
[FIND] <toy>
[GRAB] <toy>
[WALK] <filing_cabinet>
[OPEN] <filing_cabinet>
[PUTBACK] <toy> <filing_cabinet>
[CLOSE] <filing_cabinet>


Instruction:
You serve as an AI task planner.
1. Your task is to create a plan to achieve a goal by converting it into a sequence of actions. Each action should follow the format "[verb] <target1> <target2>", where 'verb' represents the action, and 'target1' and 'target2' are optional arguments.
2. You must describe your plan in natural language at the beginning. After that, you should list all the actions together.
Ensure that you response can be parsed by Python json.loads.

Here is an example plan to achieve a goal for reference:
Scene_Objects:['dry_pasta', 'filing_cabinet', 'walllamp', 'toothbrush', 'drawing', 'wallshelf', 'bathroom_counter', 'floor', 'ceiling', 'bookshelf', 'clothes_jacket', 'mat', 'tvstand', 'ceilinglamp', 'window', 'couch', 'pillow', 'wall', 'bench', 'box', 'cup', 'photoframe', 'novel', 'mouthwash', 'television', 'curtain', 'doorjamb', 'comb', 'light', 'table']
Task:Read book
response:
{
    "thoughts": Sit and read,
    "actions": ['[WALK] <home_office>', '[WALK] <filing_cabinet>', '[OPEN] <filing_cabinet>', '[FIND] <novel>', '[GRAB] <novel>', '[CLOSE] <filing_cabinet>', '[WALK] <couch>', '[SIT] <couch>', '[READ] <novel>']
}

Input:
Scene_Objects:['filing_cabinet', 'mop', 'band-aids', 'drawing', 'food_egg', 'bathroom_counter', 'floor', 'phone', 'cleaning_solution', 'bookshelf', 'computer', 'stereo', 'oil', 'mousepad', 'wall', 'wall_clock', 'nightstand', 'shelf', 'newspaper', 'food_food', 'video_game_controller', 'coin', 'rag', 'mouse', 'pencil', 'bathtub', 'bathroom_cabinet', 'light', 'coffee', 'creditcard']
Task:Clean  mirror
response:

GET CLEANING CLOTH, SPRAY CLEANER ON CLOTH, CLEAN MIRROR

[WALK] <bathroom>
[WALK] <cleaning_solution>
[FIND] <cleaning_solution>
[GRAB] <cleaning_solution>
[FIND] <rag>
[GRAB] <rag>
[POUR] <cleaning_solution> <rag>
[PUTOBJBACK] <cleaning_solution>
[WALK] <mirror>
[WIPE] <mirror>
[WIPE] <mirror>
[WIPE] <mirror>
[PUTOBJBACK] <rag>


Instruction:
You serve as an AI task planner.
1. Your task is to create a plan to achieve a goal by converting it into a sequence of actions. Each action should follow the format "[verb] <target1> <target2>", where 'verb' represents the action, and 'target1' and 'target2' are optional arguments.
2. You must describe your plan in natural language at the beginning. After that, you should list all the actions together.
Ensure that you response can be parsed by Python json.loads.

Here is an example plan to achieve a goal for reference:
Scene_Objects:['dry_pasta', 'bathroom', 'ceilingfan', 'knife', 'drawing', 'needle', 'knifeblock', 'bathroom_counter', 'shampoo', 'floor', 'ceiling', 'phone', 'piano_bench', 'faucet', 'window', 'teeth', 'clothes_pants', 'wall', 'photoframe', 'check', 'oven_mitts', 'tray', 'pencil', 'clothes_dress', 'sink', 'bathroom_cabinet', 'home_office', 'clothes_skirt', 'soap', 'hands_both']
Task:Wash hands
response:
{
    "thoughts": Go to the bathroom and to the sink, turn the faucet on, push the bottle of soap onto your hands and scrub them. Then rinse your hands out and turn the faucet off.,
    "actions": ['[WALK] <bathroom>', '[WALK] <sink>', '[FIND] <sink>', '[FIND] <faucet>', '[SWITCHON] <faucet>', '[FIND] <soap>', '[PUSH] <soap>', '[FIND] <hands_both>', '[SCRUB] <hands_both>', '[RINSE] <hands_both>', '[SWITCHOFF] <faucet>']
}

Input:
Scene_Objects:['fork', 'chair', 'milk', 'drawing', 'cpuscreen', 'shampoo', 'folder', 'bookshelf', 'computer', 'table_cloth', 'ceilinglamp', 'mat', 'oil', 'mousepad', 'couch', 'towel', 'nightstand', 'wall', 'cutting_board', 'cup', 'photoframe', 'bed', 'food_donut', 'mouse', 'kitchen_counter', 'pajamas', 'sink', 'napkin', 'home_office', 'tooth_paste']
Task:Open front door
response:

Walk over to the front door, turn the knob, and open the door.


Instruction:
You serve as an AI task planner.
1. Your task is to create a plan to achieve a goal by converting it into a sequence of actions. Each action should follow the format "[verb] <target1> <target2>", where 'verb' represents the action, and 'target1' and 'target2' are optional arguments.
2. You must describe your plan in natural language at the beginning. After that, you should list all the actions together.
Ensure that you response can be parsed by Python json.loads.

Here is an example plan to achieve a goal for reference:
Scene_Objects:['sponge', 'fork', 'filing_cabinet', 'tablelamp', 'chair', 'band-aids', 'floor', 'ceiling', 'stamp', 'alcohol', 'toaster', 'mat', 'plate', 'faucet', 'dish_soap', 'towel', 'wall', 'toy', 'bed', 'keys', 'photoframe', 'coffe_maker', 'television', 'coin', 'kitchen_counter', 'dresser', 'cupboard', 'food_steak', 'sink', 'table']
Task:Wash dishes
response:
{
    "thoughts": Run warm water in the sink. Pour dish washing liquid on the dishes. Pick up dishes and wash them individually with a sponge. Rinse suds off under running water. Dry dishes with towel.,
    "actions": ['[WALK] <dining_room>', '[WALK] <sink>', '[FIND] <faucet>', '[SWITCHON] <faucet>', '[FIND] <dish_soap>', '[GRAB] <dish_soap>', '[FIND] <sponge>', '[GRAB] <sponge>', '[POUR] <dish_soap> <sponge>', '[PUTOBJBACK] <dish_soap>', '[FIND] <plate>', '[GRAB] <plate>', '[SCRUB] <plate>', '[WASH] <plate>', '[RINSE] <plate>', '[RINSE] <sponge>', '[SWITCHOFF] <faucet>', '[PUTOBJBACK] <sponge>', '[FIND] <towel>', '[GRAB] <towel>', '[WIPE] <plate>', '[PUTOBJBACK] <towel>', '[WALK] <kitchen_cabinet>', '[OPEN] <kitchen_cabinet>', '[PUTIN] <plate> <kitchen_cabinet>', '[CLOSE] <kitchen_cabinet>']
}

Input:
Scene_Objects:['tablelamp', 'toilet', 'walllamp', 'drawing', 'floor', 'ceiling', 'bedroom', 'window', 'clothes_socks', 'couch', 'dustpan', 'clothes_pants', 'food_orange', 'food_kiwi', 'wall', 'toy', 'bed', 'photoframe', 'food_food', 'coffe_maker', 'wine', 'doorjamb', 'diary', 'console', 'mouse', 'door', 'bathroom_cabinet', 'light', 'vase', 'soap']
Task:Turn off light
response:

[WALK] <bedroom>
[WALK] <light>
[FIND] <light>
[TURNTO] <light>
[SWITCHOFF] <light>


Instruction:
You serve as an AI task planner.
1. Your task is to create a plan to achieve a goal by converting it into a sequence of actions. Each action should follow the format "[verb] <target1> <target2>", where 'verb' represents the action, and 'target1' and 'target2' are optional arguments.
2. You must describe your plan in natural language at the beginning. After that, you should list all the actions together.
Ensure that you response can be parsed by Python json.loads.

Here is an example plan to achieve a goal for reference:
Scene_Objects:['pot', 'filing_cabinet', 'freezer', 'bathroom', 'drawing', 'cpuscreen', 'floor', 'ceiling', 'phone', 'character', 'desk', 'bookshelf', 'keyboard', 'computer', 'clothes_jacket', 'table_cloth', 'mat', 'food_kiwi', 'wall', 'powersocket', 'clothes_gloves', 'food_food', 'coffe_maker', 'doorjamb', 'coffee_pot', 'headset', 'door', 'hairdryer', 'light', 'tooth_paste']
Task:Turn on light
response:
{
    "thoughts": I walk towards to the bedroom, and I open the door of the bedroom, and I switch on the lights inside the bedroom, the switch is beside the door.,
    "actions": ['[WALK] <bedroom>', '[WALK] <light>', '[FIND] <light>', '[SWITCHON] <light>']
}

Input:
Scene_Objects:['filing_cabinet', 'scissors', 'walllamp', 'orchid', 'needle', 'clothes_underwear', 'dvd_player', 'character', 'desk', 'mop_bucket', 'table_cloth', 'brush', 'ceilinglamp', 'mat', 'stereo', 'dining_room', 'nightstand', 'powersocket', 'toy', 'shelf', 'check', 'toothbrush_holder', 'mouse', 'chessboard', 'dresser', 'laundry_detergent', 'home_office', 'bathroom_cabinet', 'teeth', 'creditcard']
Task:Put toys away
response:

Pick up all the toys on the floor and put them in their correct storage bin or shelf.

[WALK] <bedroom>
[WALK] <toy>
[FIND] <toy>
[GRAB] <toy>
[WALK] <filing_cabinet>
[OPEN] <filing_cabinet>
[PUTBACK] <toy> <filing_cabinet>
[FIND] <toy>
[GRAB] <toy>
[WALK] <filing_cabinet>
[PUTBACK] <toy> <filing_cabinet>
[FIND] <toy>
[GRAB] <toy>
[WALK] <filing_cabinet>
[PUTBACK] <toy> <filing_cabinet>
[CLOSE] <filing_cabinet>


Instruction:
You serve as an AI task planner.
1. Your task is to create a plan to achieve a goal by converting it into a sequence of actions. Each action should follow the format "[verb] <target1> <target2>", where 'verb' represents the action, and 'target1' and 'target2' are optional arguments.
2. You must describe your plan in natural language at the beginning. After that, you should list all the actions together.
Ensure that you response can be parsed by Python json.loads.

Here is an example plan to achieve a goal for reference:
Scene_Objects:['pot', 'toilet', 'freezer', 'ground_coffee', 'ceilingfan', 'drawing', 'orchid', 'floor', 'ceiling', 'character', 'video_game_console', 'table_cloth', 'ceilinglamp', 'tvstand', 'balanceball', 'window', 'couch', 'dustpan', 'pillow', 'wall', 'cup', 'video_game_controller', 'television', 'curtain', 'dishrack', 'napkin', 'table', 'vase', 'scrabble', 'shoe_rack']
Task:Play games
response:
{
    "thoughts": Turn on game.  Use controller,
    "actions": ['[WALK] <home_office>', '[WALK] <television>', '[PLUGIN] <television>', '[SWITCHON] <television>', '[FIND] <video_game_console>', '[PLUGIN] <video_game_console>', '[SWITCHON] <video_game_console>', '[FIND] <video_game_console>', '[FIND] <video_game_controller>', '[GRAB] <video_game_controller>', '[WALK] <couch>', '[SIT] <couch>']
}

Input:
Scene_Objects:['filing_cabinet', 'food_bread', 'crayon', 'tea', 'freezer', 'walllamp', 'bathroom', 'detergent', 'blow_dryer', 'drawing', 'floor', 'desk', 'thread', 'mop_bucket', 'tvstand', 'towel', 'wall', 'toy', 'cup', 'check', 'razor', 'food_donut', 'wine', 'centerpiece', 'mouse', 'kitchen_counter', 'vacuum_cleaner', 'laundry_detergent', 'light', 'soap']
Task:Vacuum
response:

Robot has a vacuum underneath its feat/body that will allow it to clean the surface of the floor.


Instruction:
You serve as an AI task planner.
1. Your task is to create a plan to achieve a goal by converting it into a sequence of actions. Each action should follow the format "[verb] <target1> <target2>", where 'verb' represents the action, and 'target1' and 'target2' are optional arguments.
2. You must describe your plan in natural language at the beginning. After that, you should list all the actions together.
Ensure that you response can be parsed by Python json.loads.

Here is an example plan to achieve a goal for reference:
Scene_Objects:['glue', 'sheets', 'food_bread', 'food_pizza', 'tablelamp', 'scissors', 'toilet', 'walllamp', 'woman', 'knifeblock', 'hanger', 'bathroom_counter', 'man', 'tea_bag', 'keyboard', 'mail', 'stereo', 'window', 'couch', 'child', 'powersocket', 'photoframe', 'novel', 'coffe_maker', 'video_game_controller', 'ice', 'rag', 'headset', 'chessboard', 'maindoor']
Task:Greet guests
response:
{
    "thoughts": Greet guests when they knock on the door and invite them to enter my home,
    "actions": ['[WALK] <home_office>', '[WALK] <child>', '[FIND] <child>', '[GREET] <child>', '[FIND] <man>', '[GREET] <man>', '[FIND] <woman>', '[GREET] <woman>']
}

Input:
Scene_Objects:['filing_cabinet', 'microwave', 'freezer', 'ground_coffee', 'cpuscreen', 'floor', 'ceiling', 'keyboard', 'toaster', 'ceilinglamp', 'mat', 'faucet', 'food_orange', 'bowl', 'wall', 'wall_clock', 'cutting_board', 'bed', 'photoframe', 'coffe_maker', 'mouthwash', 'coffee_filter', 'water', 'doorjamb', 'pencil', 'kitchen_counter', 'hair', 'controller', 'sink', 'soap']
Task:Make coffee
response:

Open coffee maker. Put filter in main basket, put ground coffee in filter, fill reservoir with water, turn on coffee maker.

[WALK] <dining_room>
[WALK] <coffe_maker>
[FIND] <coffe_maker>
[OPEN] <coffe_maker>
[FIND] <coffee_filter>
[GRAB] <coffee_filter>
[PUTBACK] <coffee_filter> <coffe_maker>
[FIND] <ground_coffee>
[GRAB] <ground_coffee>
[PUTBACK] <ground_coffee> <coffe_maker>
[GRAB] <ground_coffee>
[PUTOBJBACK] <ground_coffee>
[WALK] <water>
[FIND] <water>
[GRAB] <water>
[POUR] <water> <coffe_maker>
[CLOSE] <coffe_maker>
[SWITCHON] <coffe_maker>


Instruction:
You serve as an AI task planner.
1. Your task is to create a plan to achieve a goal by converting it into a sequence of actions. Each action should follow the format "[verb] <target1> <target2>", where 'verb' represents the action, and 'target1' and 'target2' are optional arguments.
2. You must describe your plan in natural language at the beginning. After that, you should list all the actions together.
Ensure that you response can be parsed by Python json.loads.

Here is an example plan to achieve a goal for reference:
Scene_Objects:['tablelamp', 'toilet', 'walllamp', 'drawing', 'orchid', 'wallshelf', 'bathroom_counter', 'floor', 'keyboard', 'bookshelf', 'computer', 'mat', 'tvstand', 'ceilinglamp', 'window', 'mousepad', 'couch', 'pillow', 'wall', 'nightstand', 'bench', 'bed', 'check', 'television', 'tray', 'curtain', 'mouse', 'cupboard', 'door', 'table']
Task:Relax on sofa
response:
{
    "thoughts": Walk to the living room. Find the sofa. Walk to the sofa. Lie in the sofa.,
    "actions": ['[WALK] <home_office>', '[WALK] <couch>', '[FIND] <couch>', '[WALK] <couch>', '[LIE] <couch>']
}

Input:
Scene_Objects:['dry_pasta', 'microwave', 'toilet', 'freezer', 'walllamp', 'bathroom_counter', 'floor', 'ceiling', 'shampoo', 'phone', 'character', 'mail', 'food_bacon', 'stovefan', 'mat', 'mousepad', 'couch', 'dining_room', 'broom', 'wall', 'oven', 'cutting_board', 'coffe_maker', 'food_food', 'tray', 'cards', 'mouse', 'kitchen_counter', 'home_office', 'soap']
Task:Put away groceries
response:

Place groceries in refrigerator from shopping at the grocery store.

[WALK] <dining_room>
[WALK] <freezer>
[FIND] <freezer>
[OPEN] <freezer>
[FIND] <food_food>
[GRAB] <food_food>
[PUTIN] <food_food> <freezer>
[CLOSE] <freezer>


Instruction:
You serve as an AI task planner.
1. Your task is to create a plan to achieve a goal by converting it into a sequence of actions. Each action should follow the format "[verb] <target1> <target2>", where 'verb' represents the action, and 'target1' and 'target2' are optional arguments.
2. You must describe your plan in natural language at the beginning. After that, you should list all the actions together.
Ensure that you response can be parsed by Python json.loads.

Here is an example plan to achieve a goal for reference:
Scene_Objects:['sponge', 'microwave', 'walllamp', 'trashcan', 'drawing', 'floor', 'ceiling', 'button', 'toaster', 'window', 'mousepad', 'clothes_pants', 'wall', 'basket_for_clothes', 'coffe_maker', 'check', 'television', 'toothbrush_holder', 'ice', 'diary', 'mouse', 'kitchen_counter', 'vacuum_cleaner', 'cupboard', 'pajamas', 'napkin', 'coffee_cup', 'dishwasher', 'soap', 'coffee']
Task:Make coffee
response:
{
    "thoughts": Walk to the kitchen at the coffee maker, grab coffee, pour coffee into coffee maker, put coffee into coffee maker, push coffee maker's button, wait to complete, grab coffee cup,
    "actions": ['[WALK] <dining_room>', '[WALK] <coffe_maker>', '[FIND] <coffee>', '[GRAB] <coffee>', '[OPEN] <coffe_maker>', '[POUR] <coffee> <coffe_maker>', '[FIND] <coffee_cup>', '[GRAB] <coffee_cup>', '[PUTBACK] <coffee_cup> <coffe_maker>', '[FIND] <button>', '[PUSH] <button>', '[GRAB] <coffee_cup>']
}

Input:
Scene_Objects:['sponge', 'chair', 'walllamp', 'cpuscreen', 'floor', 'ceiling', 'desk', 'keyboard', 'computer', 'bookmark', 'ceilinglamp', 'tvstand', 'shower', 'mousepad', 'closetdrawer', 'wall', 'powersocket', 'oven', 'bench', 'shelf', 'check', 'television', 'curtain', 'after_shave', 'doorjamb', 'mouse', 'dresser', 'light', 'table', 'vase']
Task:Research
response:

I read different articles online to gain a better understanding of a particular business, industry, method, terminology, etc.

[WALK] <home_office>
[WALK] <computer>
[FIND] <computer>
[SWITCHON] <computer>
[TURNTO] <computer>
[LOOKAT] <computer>
[FIND] <check>
[GRAB] <check>
[READ] <check>


Instruction:
You serve as an AI task planner.
1. Your task is to create a plan to achieve a goal by converting it into a sequence of actions. Each action should follow the format "[verb] <target1> <target2>", where 'verb' represents the action, and 'target1' and 'target2' are optional arguments.
2. You must describe your plan in natural language at the beginning. After that, you should list all the actions together.
Ensure that you response can be parsed by Python json.loads.

Here is an example plan to achieve a goal for reference:
Scene_Objects:['pot', 'chair', 'freezer', 'walllamp', 'trashcan', 'drawing', 'floor', 'bookshelf', 'toaster', 'ceilinglamp', 'stereo', 'picture', 'window', 'couch', 'towel', 'wall', 'nightstand', 'oven', 'cup', 'television', 'tray', 'kitchen_counter', 'cd', 'dresser', 'hairbrush', 'cupboard', 'home_office', 'table', 'bathroom_cabinet', 'light']
Task:Listen to music
response:
{
    "thoughts": Walk to living room. Walk to radio. Switch on the radio. Walk to sofa and sit on it.,
    "actions": ['[WALK] <home_office>', '[WALK] <stereo>', '[SWITCHON] <stereo>', '[WALK] <couch>', '[SIT] <couch>']
}

Input:
Scene_Objects:['toilet', 'band-aids', 'drawing', 'orchid', 'hanger', 'bathroom_counter', 'desk', 'keyboard', 'mail', 'button', 'table_cloth', 'bookmark', 'electric_shaver', 'pillow', 'food_kiwi', 'nightstand', 'shelf', 'food_cheese', 'light_bulb', 'check', 'coffe_maker', 'razor', 'mirror', 'food_food', 'centerpiece', 'kitchen_counter', 'sink', 'bathtub', 'home_office', 'table']
Task:Shave
response:

Pick up razor.  Push the button to turn it on.  Move it in a linear motion against the beard growth.  Make sure to get the bottom of your chin, your cheeks, and mustache area.

[WALK] <bathroom>
[WALK] <electric_shaver>
[FIND] <electric_shaver>
[GRAB] <electric_shaver>
[FIND] <mirror>
[TURNTO] <mirror>
[SWITCHON] <electric_shaver>
[SWITCHOFF] <electric_shaver>
[PUTOBJBACK] <electric_shaver>


Instruction:
You serve as an AI task planner.
1. Your task is to create a plan to achieve a goal by converting it into a sequence of actions. Each action should follow the format "[verb] <target1> <target2>", where 'verb' represents the action, and 'target1' and 'target2' are optional arguments.
2. You must describe your plan in natural language at the beginning. After that, you should list all the actions together.
Ensure that you response can be parsed by Python json.loads.

Here is an example plan to achieve a goal for reference:
Scene_Objects:['spectacles', 'chair', 'bathroom', 'food_carrot', 'knifeblock', 'floor', 'phone', 'bedroom', 'envelope', 'mail', 'clothes_jacket', 'table_cloth', 'ceilinglamp', 'tvstand', 'shower', 'window', 'candle', 'microphone', 'pillow', 'basket_for_clothes', 'toilet_paper', 'check', 'rag', 'chessboard', 'laundry_detergent', 'bathroom_cabinet', 'home_office', 'tooth_paste', 'washing_machine', 'coffee']
Task:Wash clothes
response:
{
    "thoughts": Pick up my dirty clothes, load the washer, add detergent, turn on washer,
    "actions": ['[WALK] <bedroom>', '[WALK] <basket_for_clothes>', '[GRAB] <basket_for_clothes>', '[WALK] <home_office>', '[WALK] <washing_machine>', '[OPEN] <washing_machine>', '[PUTBACK] <basket_for_clothes> <washing_machine>', '[FIND] <laundry_detergent>', '[GRAB] <laundry_detergent>', '[PUTBACK] <laundry_detergent> <washing_machine>', '[RUN] <washing_machine>']
}

Input:
Scene_Objects:['microwave', 'chair', 'walllamp', 'drawing', 'cpuscreen', 'hanger', 'floor', 'ceiling', 'desk', 'keyboard', 'computer', 'stovefan', 'ceilinglamp', 'toaster', 'stereo', 'shower', 'mousepad', 'closetdrawer', 'dustpan', 'wall', 'powersocket', 'box', 'television', 'fax_machine', 'doorjamb', 'mouse', 'dresser', 'light', 'table', 'printing_paper']
Task:Print out papers
response:

Turn on printer and fill with blank paper. Use computer to click on printing option. Take printed page out of print.


Instruction:
You serve as an AI task planner.
1. Your task is to create a plan to achieve a goal by converting it into a sequence of actions. Each action should follow the format "[verb] <target1> <target2>", where 'verb' represents the action, and 'target1' and 'target2' are optional arguments.
2. You must describe your plan in natural language at the beginning. After that, you should list all the actions together.
Ensure that you response can be parsed by Python json.loads.

Here is an example plan to achieve a goal for reference:
Scene_Objects:['sheets', 'glue', 'pot', 'toilet', 'walllamp', 'drawing', 'wallshelf', 'floor', 'ceiling', 'keyboard', 'computer', 'mat', 'tvstand', 'ceilinglamp', 'couch', 'pillow', 'dining_room', 'wall', 'cup', 'photoframe', 'food_food', 'television', 'doorjamb', 'kettle', 'shaving_cream', 'kitchen_counter', 'chessboard', 'dresser', 'controller', 'light']
Task:Relax on sofa
response:
{
    "thoughts": I get home from work and walk into the living room. I see the couch and go to sit on it.,
    "actions": ['[WALK] <home_office>', '[WALK] <home_office>', '[WALK] <couch>', '[FIND] <couch>', '[TURNTO] <couch>', '[LOOKAT] <couch>', '[WALK] <couch>', '[SIT] <couch>', '[LIE] <couch>']
}

Input:
Scene_Objects:['ironing_board', 'sheets', 'glue', 'microwave', 'toilet', 'walllamp', 'blow_dryer', 'bathroom_counter', 'bedroom', 'computer', 'stovefan', 'tvstand', 'iron', 'faucet', 'mousepad', 'clothes_socks', 'couch', 'toy', 'cup', 'keys', 'coffe_maker', 'after_shave', 'towel_rack', 'mouse', 'kitchen_counter', 'controller', 'maindoor', 'bathtub', 'tooth_paste', 'clothes_shirt']
Task:Iron shirt
response:

Set up an ironing board and an iron.  Lay a shirt on board.  Run iron over shirt until it is free of wrinkles.


Instruction:
You serve as an AI task planner.
1. Your task is to create a plan to achieve a goal by converting it into a sequence of actions. Each action should follow the format "[verb] <target1> <target2>", where 'verb' represents the action, and 'target1' and 'target2' are optional arguments.
2. You must describe your plan in natural language at the beginning. After that, you should list all the actions together.
Ensure that you response can be parsed by Python json.loads.

Here is an example plan to achieve a goal for reference:
Scene_Objects:['pot', 'filing_cabinet', 'beer', 'crayon', 'detergent', 'drawing', 'food_egg', 'floor', 'ceiling', 'bedroom', 'brush', 'mat', 'ceilinglamp', 'shower', 'balanceball', 'window', 'couch', 'towel', 'wall', 'bench', 'light_bulb', 'television', 'water', 'curtain', 'mouse', 'kitchen_counter', 'door', 'home_office', 'soap', 'laser_pointer']
Task:Take shower
response:
{
    "thoughts": Walk into bathroom. Turn on shower. Take off clothing. Climb into shower. Rinse with water. Soap up body. Rinse off with water. Turn off shower. Climb out of shower. Dry off with towel.,
    "actions": ['[WALK] <bathroom>', '[WALK] <shower>', '[FIND] <shower>', '[TURNTO] <shower>', '[FIND] <water>', '[RINSE] <water>', '[FIND] <soap>', '[WASH] <soap>', '[RINSE] <water>', '[FIND] <towel>', '[GRAB] <towel>', '[SCRUB] <towel>']
}

Input:
Scene_Objects:['sheets', 'filing_cabinet', 'chair', 'cpuscreen', 'floor', 'toaster', 'mat', 'iron', 'window', 'electric_shaver', 'homework', 'clothes_socks', 'couch', 'candle', 'pillow', 'wall', 'nightstand', 'powersocket', 'toy', 'standingmirror', 'razor', 'television', 'tray', 'curtain', 'after_shave', 'doorjamb', 'mouse', 'comb', 'door', 'table']
Task:Pull up carpet
response:

Pry up a corner of your old dirty carpet.  Tug as hard as you can until it comes off the tacs. Pull up the pad. Try not to be sick at all the dirt.

[WALK] <home_office>
[WALK] <mat>
[FIND] <mat>
[TOUCH] <mat>
[PULL] <mat>


Instruction:
You serve as an AI task planner.
1. Your task is to create a plan to achieve a goal by converting it into a sequence of actions. Each action should follow the format "[verb] <target1> <target2>", where 'verb' represents the action, and 'target1' and 'target2' are optional arguments.
2. You must describe your plan in natural language at the beginning. After that, you should list all the actions together.
Ensure that you response can be parsed by Python json.loads.

Here is an example plan to achieve a goal for reference:
Scene_Objects:['fork', 'filing_cabinet', 'chair', 'trashcan', 'drawing', 'clothes_underwear', 'floor', 'phone', 'character', 'keyboard', 'mat', 'ceilinglamp', 'plate', 'tvstand', 'shower', 'faucet', 'mousepad', 'couch', 'wall', 'bench', 'powersocket', 'newspaper', 'bed', 'television', 'mouse', 'controller', 'table', 'light', 'instrument_violin', 'creditcard']
Task:Set up table
response:
{
    "thoughts": I walk to the table. I put down the dish. I put down the silverware. I put down the napkin.,
    "actions": ['[WALK] <table>', '[FIND] <fork>', '[GRAB] <fork>', '[PUTBACK] <fork> <table>', '[FIND] <fork>', '[GRAB] <fork>', '[PUTBACK] <fork> <table>', '[FIND] <fork>', '[GRAB] <fork>', '[PUTBACK] <fork> <table>', '[FIND] <fork>', '[GRAB] <fork>', '[PUTBACK] <fork> <table>', '[FIND] <fork>', '[GRAB] <fork>', '[PUTBACK] <fork> <table>', '[FIND] <plate>', '[GRAB] <plate>', '[PUTBACK] <plate> <table>', '[FIND] <plate>', '[GRAB] <plate>', '[PUTBACK] <plate> <table>', '[GRAB] <plate>', '[PUTBACK] <plate> <table>', '[GRAB] <plate>', '[PUTBACK] <plate> <table>', '[GRAB] <plate>', '[PUTBACK] <plate> <table>']
}

Input:
Scene_Objects:['filing_cabinet', 'food_carrot', 'knife', 'bathroom_counter', 'floor', 'ceiling', 'mail', 'stovefan', 'mat', 'faucet', 'mousepad', 'towel', 'pillow', 'wall', 'wall_clock', 'oven', 'toy', 'cup', 'hands_both', 'standingmirror', 'food_donut', 'tray', 'mouse', 'kitchen_counter', 'hairdryer', 'sink', 'bathroom_cabinet', 'soap', 'teeth', 'shoe_rack']
Task:Wash hands
response:

Turn faucet clockwise to turn on water.  Place hands under stream of water, pick up soap, rub hands with soap.  Put soap back down.  Rub hands together with soap on them.  Rinse hands under water from faucet.  Turn faucet counterclockwise to turn water off.  Dry hands by rubbing them on a towel.

[WALK] <bathroom>
[WALK] <sink>
[FIND] <faucet>
[SWITCHON] <faucet>
[FIND] <soap>
[GRAB] <soap>
[FIND] <hands_both>
[SCRUB] <hands_both>
[PUTOBJBACK] <soap>
[WASH] <hands_both>
[SWITCHOFF] <faucet>
[FIND] <towel>
[GRAB] <towel>
[WIPE] <hands_both>
[PUTOBJBACK] <towel>


Instruction:
You serve as an AI task planner.
1. Your task is to create a plan to achieve a goal by converting it into a sequence of actions. Each action should follow the format "[verb] <target1> <target2>", where 'verb' represents the action, and 'target1' and 'target2' are optional arguments.
2. You must describe your plan in natural language at the beginning. After that, you should list all the actions together.
Ensure that you response can be parsed by Python json.loads.

Here is an example plan to achieve a goal for reference:
Scene_Objects:['tablelamp', 'microwave', 'walllamp', 'detergent', 'trashcan', 'floor', 'ceiling', 'bedroom', 'toaster', 'mat', 'stereo', 'pillow', 'wall', 'cup', 'bed', 'coffe_maker', 'food_food', 'coffee_filter', 'water', 'food_donut', 'wooden_spoon', 'food_onion', 'doorjamb', 'pencil', 'kitchen_counter', 'cupboard', 'napkin', 'spoon', 'dishwasher', 'coffee']
Task:Make coffee
response:
{
    "thoughts": I find the coffee machine, fill it with water and coffee then press the button to make the coffee,
    "actions": ['[WALK] <dining_room>', '[WALK] <coffe_maker>', '[FIND] <coffe_maker>', '[OPEN] <coffe_maker>', '[FIND] <coffee_filter>', '[GRAB] <coffee_filter>', '[PUTBACK] <coffee_filter> <coffe_maker>', '[WALK] <coffee>', '[FIND] <coffee>', '[GRAB] <coffee>', '[POUR] <coffee> <coffe_maker>', '[WALK] <water>', '[FIND] <water>', '[GRAB] <water>', '[POUR] <water> <coffe_maker>', '[CLOSE] <coffe_maker>', '[SWITCHON] <coffe_maker>']
}

Input:
Scene_Objects:['measuring_cup', 'food_butter', 'knife', 'orchid', 'floor', 'character', 'desk', 'food_bacon', 'table_cloth', 'piano_bench', 'mat', 'picture', 'window', 'couch', 'pillow', 'bowl', 'wall', 'nightstand', 'child', 'light_bulb', 'toilet_paper', 'television', 'toothbrush_holder', 'tray', 'curtain', 'doorjamb', 'mouse', 'bathtub', 'table', 'board_game']
Task:Let baby learn how to walk
response:

The baby tries to stand up and balances on the couch and there are no sharp edges so it's safe.

[WALK] <home_office>
[WALK] <child>
[FIND] <child>
[TOUCH] <child>
[GREET] <child>
[FIND] <couch>
[TURNTO] <couch>
[POINTAT] <couch>
[TURNTO] <child>
[LOOKAT] <child>


Instruction:
You serve as an AI task planner.
1. Your task is to create a plan to achieve a goal by converting it into a sequence of actions. Each action should follow the format "[verb] <target1> <target2>", where 'verb' represents the action, and 'target1' and 'target2' are optional arguments.
2. You must describe your plan in natural language at the beginning. After that, you should list all the actions together.
Ensure that you response can be parsed by Python json.loads.

Here is an example plan to achieve a goal for reference:
Scene_Objects:['glue', 'tablelamp', 'mop', 'toilet', 'chair', 'trashcan', 'knifeblock', 'hanger', 'longboard', 'floor', 'phone', 'keyboard', 'balanceball', 'foundation', 'pillow', 'wall', 'powersocket', 'box', 'photoframe', 'bed', 'check', 'rag', 'doorjamb', 'kitchen_counter', 'dresser', 'cupboard', 'door', 'maindoor', 'light', 'colander']
Task:Sit
response:
{
    "thoughts": We sit at the dining room table,
    "actions": ['[WALK] <dining_room>', '[WALK] <chair>', '[FIND] <chair>', '[PULL] <chair>', '[SIT] <chair>']
}

Input:
Scene_Objects:['scissors', 'microwave', 'toilet', 'knife', 'bathroom_counter', 'floor', 'ceiling', 'mop_bucket', 'stovefan', 'mat', 'faucet', 'mousepad', 'towel', 'wall', 'wall_clock', 'oven', 'bench', 'cutting_board', 'shelf', 'food_rice', 'tray', 'after_shave', 'towel_rack', 'kitchen_counter', 'sink', 'bathroom_cabinet', 'soap', 'laser_pointer', 'dirt', 'hands_both']
Task:Hand washing
response:

Turn on the faucet. Soap up your hands. Then rinse under the running water of the faucet. Turn off faucet and dry hands.

[WALK] <bathroom>
[WALK] <sink>
[FIND] <faucet>
[SWITCHON] <faucet>
[FIND] <soap>
[GRAB] <soap>
[FIND] <hands_both>
[SCRUB] <hands_both>
[PUTOBJBACK] <soap>
[WASH] <hands_both>
[SWITCHOFF] <faucet>
[FIND] <towel>
[GRAB] <towel>
[WIPE] <hands_both>


Instruction:
You serve as an AI task planner.
1. Your task is to create a plan to achieve a goal by converting it into a sequence of actions. Each action should follow the format "[verb] <target1> <target2>", where 'verb' represents the action, and 'target1' and 'target2' are optional arguments.
2. You must describe your plan in natural language at the beginning. After that, you should list all the actions together.
Ensure that you response can be parsed by Python json.loads.

Here is an example plan to achieve a goal for reference:
Scene_Objects:['fork', 'filing_cabinet', 'blow_dryer', 'cat', 'wallshelf', 'ceiling', 'desk', 'bedroom', 'keyboard', 'stovefan', 'mousepad', 'powersocket', 'oven', 'bed', 'food_food', 'check', 'wooden_spoon', 'towel_rack', 'mouse', 'dishrack', 'comb', 'maindoor', 'bathtub', 'napkin', 'home_office', 'light', 'table', 'soap', 'laser_pointer', 'scrabble']
Task:Read book
response:
{
    "thoughts": Open coffee maker. Put filter in main basket, put ground coffee in filter, fill reservoir with water, turn on coffee maker.,
    "actions": ['[WALK] <home_office>', '[WALK] <address_book>', '[FIND] <address_book>', '[GRAB] <address_book>', '[READ] <address_book>']
}

Input:
Scene_Objects:['microwave', 'chair', 'freezer', 'detergent', 'food_carrot', 'orchid', 'floor', 'wine_glass', 'food_cake', 'mat', 'picture', 'window', 'mousepad', 'couch', 'clothes_hat', 'pillow', 'wall', 'pasta', 'shelf', 'food_cheese', 'newspaper', 'food_food', 'television', 'curtain', 'doorjamb', 'kitchen_counter', 'dresser', 'bathtub', 'table', 'vase']
Task:Entertain
response:

Give guests wine, cheese, crackers and sit and talk

[WALK] <home_office>
[WALK] <food_cheese>
[FIND] <food_cheese>
[FIND] <food_food>
[FIND] <couch>
[SIT] <couch>
[FIND] <wine_glass>
[GRAB] <wine_glass>
[DRINK] <wine_glass>


Instruction:
You serve as an AI task planner.
1. Your task is to create a plan to achieve a goal by converting it into a sequence of actions. Each action should follow the format "[verb] <target1> <target2>", where 'verb' represents the action, and 'target1' and 'target2' are optional arguments.
2. You must describe your plan in natural language at the beginning. After that, you should list all the actions together.
Ensure that you response can be parsed by Python json.loads.

Here is an example plan to achieve a goal for reference:
Scene_Objects:['pot', 'tablelamp', 'drawing', 'needle', 'knife', 'clothes_underwear', 'hanger', 'floor', 'envelope', 'computer', 'ceilinglamp', 'oil', 'mousepad', 'pillow', 'bowl', 'wall', 'nightstand', 'child', 'bed', 'novel', 'food_food', 'coffe_maker', 'television', 'doorjamb', 'dishrack', 'comb', 'laundry_detergent', 'conditioner', 'sink', 'instrument_violin']
Task:Story reading time
response:
{
    "thoughts": Sit on bed with child, open mother goose, pick story, read book, point at the pretty pictures,
    "actions": ['[WALK] <bedroom>', '[WALK] <child>', '[FIND] <child>', '[GREET] <child>', '[FIND] <novel>', '[GRAB] <novel>', '[FIND] <bed>', '[SIT] <bed>', '[TURNTO] <child>', '[LOOKAT] <child>', '[TURNTO] <novel>', '[POINTAT] <novel>', '[READ] <novel>']
}

Input:
Scene_Objects:['blender', 'wallshelf', 'hanger', 'floor', 'phone', 'ceiling', 'clothes_jacket', 'table_cloth', 'mat', 'floor_lamp', 'window', 'couch', 'pillow', 'wall', 'nightstand', 'light_bulb', 'novel', 'mouthwash', 'television', 'ice', 'curtain', 'after_shave', 'doorjamb', 'console', 'kettle', 'conditioner', 'bathtub', 'sink', 'table', 'vase']
Task:Read book
response:

A person brings a book into the living room and sits down in a comfortable chair.  If it is dark in the room the person turns on the lamp. The book is opened to the next page to be read.  The person begins reading the book until they need to stop for some reason.

[WALK] <home_office>
[WALK] <novel>
[FIND] <novel>
[GRAB] <novel>
[FIND] <couch>
[SIT] <couch>
[FIND] <floor_lamp>
[SWITCHON] <floor_lamp>
[READ] <novel>


Instruction:
You serve as an AI task planner.
1. Your task is to create a plan to achieve a goal by converting it into a sequence of actions. Each action should follow the format "[verb] <target1> <target2>", where 'verb' represents the action, and 'target1' and 'target2' are optional arguments.
2. You must describe your plan in natural language at the beginning. After that, you should list all the actions together.
Ensure that you response can be parsed by Python json.loads.

Here is an example plan to achieve a goal for reference:
Scene_Objects:['glue', 'trashcan', 'orchid', 'knifeblock', 'floor', 'tea_bag', 'keyboard', 'computer', 'stovefan', 'tvstand', 'stereo', 'window', 'dustpan', 'candle', 'food_jam', 'wall', 'pasta', 'bed', 'photoframe', 'coffe_maker', 'television', 'tray', 'curtain', 'wooden_spoon', 'towel_rack', 'pencil', 'chessboard', 'cupboard', 'maindoor', 'light']
Task:Listen to music
response:
{
    "thoughts": Put iPhone into speaker holder, open up the Pandora app, listen to music.,
    "actions": ['[WALK] <bedroom>', '[WALK] <phone>', '[FIND] <phone>', '[GRAB] <phone>', '[WALK] <stereo>', '[PLUGIN] <phone>', '[SWITCHON] <stereo>', '[FIND] <bed>', '[SIT] <bed>']
}

Input:
Scene_Objects:['food_bread', 'filing_cabinet', 'food_ice_cream', 'beer', 'microwave', 'toilet', 'freezer', 'walllamp', 'food_egg', 'floor', 'ceiling', 'phone', 'keyboard', 'toaster', 'stovefan', 'brush', 'faucet', 'food_peanut_butter', 'clothes_pants', 'wall', 'oven', 'powersocket', 'cutting_board', 'food_cheese', 'coffe_maker', 'food_food', 'tray', 'kitchen_counter', 'comb', 'sink']
Task:Make toast
response:

Place slices of bread in a toaster ,wait for the bread to pop up .Set aside.

[WALK] <dining_room>
[WALK] <freezer>
[FIND] <freezer>
[OPEN] <freezer>
[FIND] <food_bread>
[GRAB] <food_bread>
[CLOSE] <freezer>
[FIND] <toaster>
[PLUGIN] <toaster>
[PUTBACK] <food_bread> <toaster>
[SWITCHON] <toaster>


Instruction:
You serve as an AI task planner.
1. Your task is to create a plan to achieve a goal by converting it into a sequence of actions. Each action should follow the format "[verb] <target1> <target2>", where 'verb' represents the action, and 'target1' and 'target2' are optional arguments.
2. You must describe your plan in natural language at the beginning. After that, you should list all the actions together.
Ensure that you response can be parsed by Python json.loads.

Here is an example plan to achieve a goal for reference:
Scene_Objects:['juice', 'measuring_cup', 'microwave', 'freezer', 'drawing', 'bathroom_counter', 'floor', 'ceiling', 'phone', 'desk', 'face', 'mop_bucket', 'tvstand', 'faucet', 'food_peanut_butter', 'towel', 'wall', 'oven', 'face_soap', 'tape', 'photoframe', 'bed', 'keys', 'rag', 'cards', 'comb', 'cupboard', 'sink', 'spoon', 'bathroom_cabinet']
Task:Wash face
response:
{
    "thoughts": Turn on water faucet. Get rag wet. Get face soap out. Squirt face soap in hands and put it on face. Rub soap into face. Wash soap off of face. Dry face off on the hand towel. Hang out rag and hand towel.,
    "actions": ['[WALK] <bathroom>', '[WALK] <sink>', '[FIND] <rag>', '[GRAB] <rag>', '[FIND] <faucet>', '[SWITCHON] <faucet>', '[WASH] <rag>', '[FIND] <face_soap>', '[GRAB] <face_soap>', '[POUR] <face_soap> <rag>', '[PUTOBJBACK] <face_soap>', '[FIND] <face>', '[SCRUB] <face>', '[PUTBACK] <rag> <sink>', '[RINSE] <face>', '[RINSE] <rag>', '[SWITCHOFF] <faucet>', '[GRAB] <rag>', '[PUTOBJBACK] <rag>', '[FIND] <towel>', '[GRAB] <towel>', '[WIPE] <face>', '[PUTOBJBACK] <towel>']
}

Input:
Scene_Objects:['spectacles', 'cpuscreen', 'hanger', 'floor', 'ceiling', 'phone', 'legs_both', 'desk', 'keyboard', 'face', 'computer', 'toaster', 'mousepad', 'closetdrawer', 'dustpan', 'towel', 'wall', 'feet_both', 'powersocket', 'arms_both', 'basket_for_clothes', 'cup', 'check', 'mouse', 'shoes', 'dresser', 'hairbrush', 'controller', 'light', 'clothes_shirt']
Task:Try yourself off
response:

After your shower, go into your bedroom and use a towel to dry water off of yourself before dressing.

[WALK] <bedroom>
[WALK] <dresser>
[FIND] <dresser>
[OPEN] <dresser>
[FIND] <towel>
[GRAB] <towel>
[CLOSE] <dresser>
[FIND] <face>
[WIPE] <face>
[FIND] <arms_both>
[WIPE] <arms_both>
[FIND] <legs_both>
[WIPE] <legs_both>
[FIND] <feet_both>
[WIPE] <feet_both>
[FIND] <basket_for_clothes>
[PUTBACK] <towel> <basket_for_clothes>


Instruction:
You serve as an AI task planner.
1. Your task is to create a plan to achieve a goal by converting it into a sequence of actions. Each action should follow the format "[verb] <target1> <target2>", where 'verb' represents the action, and 'target1' and 'target2' are optional arguments.
2. You must describe your plan in natural language at the beginning. After that, you should list all the actions together.
Ensure that you response can be parsed by Python json.loads.

Here is an example plan to achieve a goal for reference:
Scene_Objects:['filing_cabinet', 'chair', 'ground_coffee', 'detergent', 'cpuscreen', 'hanger', 'floor', 'ceiling', 'folder', 'purse', 'computer', 'toaster', 'laptop', 'shower', 'picture', 'couch', 'wall', 'pasta', 'nightstand', 'box', 'photoframe', 'coffe_maker', 'television', 'coffee_filter', 'tray', 'kitchen_counter', 'cupboard', 'sink', 'dishwasher', 'instrument_violin']
Task:Make coffee
response:
{
    "thoughts": Open the coffee maker and put a filer, grab ground coffee and put it in the coffee maker, then close the coffee maker and switch it on,
    "actions": ['[WALK] <dining_room>', '[WALK] <coffe_maker>', '[FIND] <coffe_maker>', '[OPEN] <coffe_maker>', '[FIND] <coffee_filter>', '[GRAB] <coffee_filter>', '[PUTBACK] <coffee_filter> <coffe_maker>', '[FIND] <ground_coffee>', '[GRAB] <ground_coffee>', '[FIND] <ground_coffee>', '[PUTBACK] <ground_coffee> <coffe_maker>', '[CLOSE] <coffe_maker>', '[SWITCHON] <coffe_maker>']
}

Input:
Scene_Objects:['pot', 'tea', 'walllamp', 'bathroom', 'wallshelf', 'ceiling', 'dvd_player', 'tea_bag', 'food_bacon', 'toaster', 'homework', 'clothes_pants', 'nightstand', 'wall', 'powersocket', 'toy', 'newspaper', 'standingmirror', 'novel', 'bed', 'console', 'mouse', 'shoes', 'controller', 'door', 'sink', 'bathtub', 'home_office', 'table', 'vase']
Task:Watch fly
response:

Look around for a fly, often on a wall or ceiling.  Follow it's movements.

[WALK] <bedroom>
[WALK] <fly>
[FIND] <fly>
[TURNTO] <fly>
[LOOKAT] <fly>


Instruction:
You serve as an AI task planner.
1. Your task is to create a plan to achieve a goal by converting it into a sequence of actions. Each action should follow the format "[verb] <target1> <target2>", where 'verb' represents the action, and 'target1' and 'target2' are optional arguments.
2. You must describe your plan in natural language at the beginning. After that, you should list all the actions together.
Ensure that you response can be parsed by Python json.loads.

Here is an example plan to achieve a goal for reference:
Scene_Objects:['dry_pasta', 'walllamp', 'ceilingfan', 'drawing', 'floor', 'ceiling', 'bookshelf', 'stovefan', 'ceilinglamp', 'tvstand', 'balanceball', 'mat', 'window', 'foundation', 'couch', 'wall', 'pasta', 'toy', 'box', 'television', 'curtain', 'diary', 'towel_rack', 'kitchen_counter', 'cupboard', 'clothes_scarf', 'home_office', 'table', 'vase', 'coffee']
Task:Change TV channels
response:
{
    "thoughts": Take remote. Change to desired channel by you.,
    "actions": ['[WALK] <home_office>', '[WALK] <remote_control>', '[FIND] <remote_control>', '[GRAB] <remote_control>', '[WALK] <couch>', '[SIT] <couch>', '[TOUCH] <remote_control>', '[TOUCH] <remote_control>', '[TOUCH] <remote_control>', '[FIND] <television>', '[TURNTO] <television>', '[LOOKAT] <television>', '[WATCH] <television>', '[WATCH] <television>', '[WATCH] <television>']
}

Input:
Scene_Objects:['fork', 'tablelamp', 'juice', 'nail_polish', 'drawing', 'bathroom_counter', 'floor', 'ceiling', 'phone', 'character', 'bedroom', 'mat', 'shower', 'window', 'closetdrawer', 'wall', 'nightstand', 'cutting_board', 'bed', 'photoframe', 'coffe_maker', 'television', 'curtain', 'mouse', 'pencil', 'vacuum_cleaner', 'hair', 'maindoor', 'table', 'vase']
Task:Read book
response:

[WALK] <bedroom>
[WALK] <novel>
[FIND] <novel>
[GRAB] <novel>
[WALK] <bed>
[LIE] <bed>
[READ] <novel>


Instruction:
You serve as an AI task planner.
1. Your task is to create a plan to achieve a goal by converting it into a sequence of actions. Each action should follow the format "[verb] <target1> <target2>", where 'verb' represents the action, and 'target1' and 'target2' are optional arguments.
2. You must describe your plan in natural language at the beginning. After that, you should list all the actions together.
Ensure that you response can be parsed by Python json.loads.

Here is an example plan to achieve a goal for reference:
Scene_Objects:['toilet', 'walllamp', 'drawing', 'orchid', 'cpuscreen', 'floor', 'ceiling', 'character', 'remote_control', 'stovefan', 'ceilinglamp', 'tvstand', 'mat', 'window', 'couch', 'pillow', 'wall', 'powersocket', 'television', 'tray', 'curtain', 'doorjamb', 'dresser', 'hairbrush', 'clothes_dress', 'door', 'sink', 'spoon', 'table', 'light']
Task:Change TV channel
response:
{
    "thoughts": I walk into the living room. I sit on the couch and grab the remote. Then I turn on the TV and change the channel.,
    "actions": ['[WALK] <home_office>', '[WALK] <couch>', '[FIND] <couch>', '[SIT] <couch>', '[FIND] <remote_control>', '[GRAB] <remote_control>', '[FIND] <television>', '[SWITCHON] <television>']
}

Input:
Scene_Objects:['sponge', 'tablelamp', 'detergent', 'wallshelf', 'hanger', 'floor', 'phone', 'shampoo', 'character', 'desk', 'mop_bucket', 'bookmark', 'toaster', 'mat', 'window', 'couch', 'pillow', 'dining_room', 'food_kiwi', 'wall', 'nightstand', 'mouthwash', 'television', 'razor', 'curtain', 'after_shave', 'doorjamb', 'bathroom_cabinet', 'table', 'light']
Task:Read book
response:

Pick up a book and open to the last page you were on. Read the book.

[WALK] <home_office>
[WALK] <novel>
[FIND] <novel>
[GRAB] <novel>
[WALK] <couch>
[SIT] <couch>
[FIND] <bookmark>
[READ] <novel>


Instruction:
You serve as an AI task planner.
1. Your task is to create a plan to achieve a goal by converting it into a sequence of actions. Each action should follow the format "[verb] <target1> <target2>", where 'verb' represents the action, and 'target1' and 'target2' are optional arguments.
2. You must describe your plan in natural language at the beginning. After that, you should list all the actions together.
Ensure that you response can be parsed by Python json.loads.

Here is an example plan to achieve a goal for reference:
Scene_Objects:['tablelamp', 'chair', 'cat', 'ceilingfan', 'cpuscreen', 'floor', 'ceiling', 'desk', 'bookshelf', 'keyboard', 'computer', 'ceilinglamp', 'mousepad', 'oil', 'couch', 'wall', 'wall_clock', 'powersocket', 'oven', 'bench', 'newspaper', 'mouthwash', 'television', 'diary', 'towel_rack', 'mouse', 'dresser', 'hairbrush', 'hairdryer', 'soap']
Task:Check email
response:
{
    "thoughts": Sit in teak deck chair, have wooden drawing board on lap, laptop on wooden drawing board, log in to my two email accounts, go through new emails and respond.,
    "actions": ['[WALK] <home_office>', '[WALK] <laptop>', '[FIND] <laptop>', '[GRAB] <laptop>', '[WALK] <chair>', '[SIT] <chair>', '[SWITCHON] <laptop>', '[TURNTO] <laptop>', '[LOOKAT] <laptop>', '[TOUCH] <laptop>', '[TURNTO] <laptop>', '[LOOKAT] <laptop>', '[TOUCH] <laptop>', '[TURNTO] <laptop>', '[LOOKAT] <laptop>', '[TOUCH] <laptop>', '[TURNTO] <laptop>', '[LOOKAT] <laptop>', '[TOUCH] <laptop>']
}

Input:
Scene_Objects:['microwave', 'cpuscreen', 'hanger', 'floor', 'ceiling', 'desk', 'keyboard', 'bookshelf', 'computer', 'plate', 'iron', 'mousepad', 'closetdrawer', 'wall', 'wall_clock', 'powersocket', 'cutting_board', 'clothes_gloves', 'check', 'coffe_maker', 'food_food', 'curtain', 'food_onion', 'mouse', 'comb', 'dresser', 'clothes_dress', 'sink', 'light', 'coffee']
Task:Hang up jacket
response:

I put clothes on hangers and hang them in the closet

[WALK] <bedroom>
[WALK] <clothes_dress>
[FIND] <clothes_dress>
[GRAB] <clothes_dress>
[WALK] <dresser>
[FIND] <hanger>
[OPEN] <dresser>
[PUTIN] <clothes_dress> <dresser>
[FIND] <clothes_dress>
[GRAB] <clothes_dress>
[WALK] <dresser>
[PUTIN] <clothes_dress> <dresser>
[CLOSE] <dresser>


Instruction:
You serve as an AI task planner.
1. Your task is to create a plan to achieve a goal by converting it into a sequence of actions. Each action should follow the format "[verb] <target1> <target2>", where 'verb' represents the action, and 'target1' and 'target2' are optional arguments.
2. You must describe your plan in natural language at the beginning. After that, you should list all the actions together.
Ensure that you response can be parsed by Python json.loads.

Here is an example plan to achieve a goal for reference:
Scene_Objects:['pot', 'juice', 'jelly', 'freezer', 'walllamp', 'nail_polish', 'knifeblock', 'drawing', 'cpuscreen', 'floor', 'ceiling', 'desk', 'keyboard', 'computer', 'button', 'stovefan', 'ceilinglamp', 'mat', 'faucet', 'mousepad', 'pillow', 'wall', 'oven', 'powersocket', 'bench', 'cup', 'food_food', 'food_rice', 'tray', 'doorjamb', 'mouse', 'kitchen_counter', 'cupboard', 'door', 'sink', 'light', 'table', 'board_game']
Task:Grab some juice
response:
{
    "thoughts": I go to the fridge, and grab some juice out of it. I then get a glass, and pour the juice into the glass.,
    "actions": ['[WALK] <dining_room>', '[WALK] <cupboard>', '[FIND] <cupboard>', '[OPEN] <cupboard>', '[FIND] <cup>', '[GRAB] <cup>', '[CLOSE] <cupboard>', '[WALK] <freezer>', '[OPEN] <freezer>', '[FIND] <juice>', '[GRAB] <juice>', '[POUR] <juice> <cup>', '[PUTOBJBACK] <juice>', '[CLOSE] <freezer>', '[FIND] <table>', '[PUTBACK] <cup> <table>']
}

Input:
Scene_Objects:['pot', 'tablelamp', 'chair', 'toothbrush', 'wallshelf', 'bathroom_counter', 'floor', 'ceiling', 'bookshelf', 'stovefan', 'mat', 'faucet', 'window', 'towel', 'pillow', 'wall', 'wall_clock', 'oven', 'bench', 'cutting_board', 'television', 'food_rice', 'ice', 'wooden_spoon', 'tray', 'comb', 'sink', 'bathroom_cabinet', 'tooth_paste', 'teeth']
Task:Brush teeth
response:

Put toothpaste on toothbrush, brush teeth, rinse mouth

[WALK] <bathroom>
[WALK] <toothbrush>
[FIND] <toothbrush>
[GRAB] <toothbrush>
[FIND] <tooth_paste>
[GRAB] <tooth_paste>
[POUR] <tooth_paste> <toothbrush>
[PUTOBJBACK] <tooth_paste>
[WALK] <sink>
[FIND] <teeth>
[SCRUB] <teeth>
[SCRUB] <teeth>
[SCRUB] <teeth>
[PUTBACK] <toothbrush> <sink>
[FIND] <faucet>
[SWITCHON] <faucet>
[RINSE] <toothbrush>
[RINSE] <teeth>
[SWITCHOFF] <faucet>
[GRAB] <toothbrush>
[PUTOBJBACK] <toothbrush>


Instruction:
You serve as an AI task planner.
1. Your task is to create a plan to achieve a goal by converting it into a sequence of actions. Each action should follow the format "[verb] <target1> <target2>", where 'verb' represents the action, and 'target1' and 'target2' are optional arguments.
2. You must describe your plan in natural language at the beginning. After that, you should list all the actions together.
Ensure that you response can be parsed by Python json.loads.

Here is an example plan to achieve a goal for reference:
Scene_Objects:['fork', 'pot', 'microwave', 'toilet', 'cat', 'wallshelf', 'bathroom_counter', 'floor', 'dvd_player', 'bookshelf', 'stovefan', 'ceilinglamp', 'toaster', 'mat', 'shower', 'faucet', 'tvstand', 'couch', 'towel', 'wall', 'bench', 'cutting_board', 'bed', 'razor', 'television', 'curtain', 'kitchen_counter', 'dresser', 'home_office', 'light']
Task:Pet cat
response:
{
    "thoughts": Pet Cat,
    "actions": ['[WALK] <home_office>', '[WALK] <cat>', '[FIND] <cat>', '[WALK] <cat>', '[TURNTO] <cat>', '[LOOKAT] <cat>', '[TOUCH] <cat>']
}

Input:
Scene_Objects:['spectacles', 'filing_cabinet', 'food_salt', 'chair', 'walllamp', 'drawing', 'cpuscreen', 'clothes_underwear', 'hanger', 'floor', 'ceiling', 'desk', 'bookshelf', 'keyboard', 'computer', 'mat', 'deck_of_cards', 'window', 'mousepad', 'closetdrawer', 'couch', 'pillow', 'wall', 'pasta', 'powersocket', 'toy', 'tape', 'light_bulb', 'check', 'food_food', 'television', 'curtain', 'doorjamb', 'mouse', 'pencil', 'dresser', 'conditioner', 'spoon', 'light', 'table', 'colander']
Task:Re arrange office
response:

Walk in.Turn on light.Move furniture. Change the room

[WALK] <home_office>
[WALK] <light>
[FIND] <light>
[SWITCHON] <light>
[WALK] <desk>
[PUSH] <desk>
[WALK] <chair>
[PUSH] <chair>
[WALK] <couch>
[PUSH] <couch>
[WALK] <filing_cabinet>
[PUSH] <filing_cabinet>


Instruction:
You serve as an AI task planner.
1. Your task is to create a plan to achieve a goal by converting it into a sequence of actions. Each action should follow the format "[verb] <target1> <target2>", where 'verb' represents the action, and 'target1' and 'target2' are optional arguments.
2. You must describe your plan in natural language at the beginning. After that, you should list all the actions together.
Ensure that you response can be parsed by Python json.loads.

Here is an example plan to achieve a goal for reference:
Scene_Objects:['tablelamp', 'crayon', 'jelly', 'freezer', 'bathroom', 'drawing', 'bathroom_counter', 'floor', 'ceiling', 'phone', 'food_cake', 'mop_bucket', 'stovefan', 'mat', 'ceilinglamp', 'closetdrawer', 'couch', 'pillow', 'broom', 'wall', 'food_food', 'television', 'wine', 'tray', 'kitchen_counter', 'cupboard', 'home_office', 'table', 'light', 'clothes_skirt']
Task:Put groceries in Fridge
response:
{
    "thoughts": Go to kitchen, open fridge, get groceries, put groceries in fridge, close fridge,
    "actions": ['[WALK] <dining_room>', '[WALK] <freezer>', '[FIND] <freezer>', '[OPEN] <freezer>', '[FIND] <food_food>', '[GRAB] <food_food>', '[PUTIN] <food_food> <freezer>', '[CLOSE] <freezer>']
}

Input:
Scene_Objects:['food_ice_cream', 'bathroom', 'food_carrot', 'wallshelf', 'hanger', 'bathroom_counter', 'floor', 'stamp', 'faucet', 'stereo', 'shower', 'oil', 'closetdrawer', 'microphone', 'clothes_hat', 'wall', 'nightstand', 'oven', 'tape', 'cup', 'keys', 'toilet_paper', 'curtain', 'shoes', 'maindoor', 'sink', 'bathtub', 'food_steak', 'light', 'coffee']
Task:Take dishes out of dishwasher
response:

Take clean dishes out of the dishwasher and put away

[WALK] <dining_room>
[WALK] <dishwasher>
[OPEN] <dishwasher>
[CLOSE] <dishwasher>


Instruction:
You serve as an AI task planner.
1. Your task is to create a plan to achieve a goal by converting it into a sequence of actions. Each action should follow the format "[verb] <target1> <target2>", where 'verb' represents the action, and 'target1' and 'target2' are optional arguments.
2. You must describe your plan in natural language at the beginning. After that, you should list all the actions together.
Ensure that you response can be parsed by Python json.loads.

Here is an example plan to achieve a goal for reference:
Scene_Objects:['microwave', 'chair', 'dog', 'walllamp', 'trashcan', 'cpuscreen', 'floor', 'ceiling', 'desk', 'bedroom', 'keyboard', 'computer', 'table_cloth', 'ceilinglamp', 'tvstand', 'faucet', 'mousepad', 'couch', 'form', 'wall', 'powersocket', 'photoframe', 'mouthwash', 'television', 'doorjamb', 'mouse', 'cupboard', 'bathtub', 'sink', 'table']
Task:Work
response:
{
    "thoughts": go to home office. turn the computer on. begin working,
    "actions": ['[WALK] <home_office>', '[WALK] <computer>', '[FIND] <computer>', '[SWITCHON] <computer>']
}

Input:
Scene_Objects:['dry_pasta', 'food_ice_cream', 'toothbrush', 'drawing', 'hanger', 'bathroom_counter', 'floor', 'ceiling', 'phone', 'bedroom', 'bookshelf', 'alcohol', 'brush', 'shoe-shine_kit', 'faucet', 'mousepad', 'closetdrawer', 'candle', 'clothes_pants', 'wall', 'standingmirror', 'food_food', 'television', 'tray', 'coffee_pot', 'towel_rack', 'dresser', 'bathtub', 'bathroom_cabinet', 'vase']
Task:Dust
response:

Using soft brush, carefully dust both Indonesian wedding doll statues.

[WALK] <home_office>
[WALK] <dresser>
[OPEN] <dresser>
[FIND] <brush>
[GRAB] <brush>
[CLOSE] <dresser>


Instruction:
You serve as an AI task planner.
1. Your task is to create a plan to achieve a goal by converting it into a sequence of actions. Each action should follow the format "[verb] <target1> <target2>", where 'verb' represents the action, and 'target1' and 'target2' are optional arguments.
2. You must describe your plan in natural language at the beginning. After that, you should list all the actions together.
Ensure that you response can be parsed by Python json.loads.

Here is an example plan to achieve a goal for reference:
Scene_Objects:['pot', 'food_bread', 'filing_cabinet', 'tablelamp', 'crayon', 'woman', 'wallshelf', 'shampoo', 'floor', 'phone', 'desk', 'man', 'bookshelf', 'closetdrawer', 'couch', 'dining_room', 'nightstand', 'child', 'bed', 'photoframe', 'standingmirror', 'toilet_paper', 'oven_mitts', 'towel_rack', 'kitchen_counter', 'dresser', 'sink', 'bathroom_cabinet', 'clothes_skirt', 'vase']
Task:Say goodbye to guests leaving
response:
{
    "thoughts": Tell them bye,
    "actions": ['[WALK] <home_office>', '[WALK] <child>', '[FIND] <child>', '[TOUCH] <child>', '[FIND] <man>', '[TOUCH] <man>', '[FIND] <woman>', '[TOUCH] <woman>']
}

Input:
Scene_Objects:['food_bread', 'chair', 'cpuscreen', 'ceiling', 'character', 'video_game_console', 'bookshelf', 'keyboard', 'computer', 'mat', 'faucet', 'window', 'mousepad', 'wall_clock', 'tape', 'cutting_board', 'food_cheese', 'check', 'video_game_controller', 'mouthwash', 'food_onion', 'rag', 'coffee_pot', 'towel_rack', 'pencil', 'vacuum_cleaner', 'cd', 'dresser', 'home_office', 'dirt']
Task:Playing video game
response:

Playing  video games  on various video game  systems such as wii u  and  xbox

[WALK] <home_office>
[WALK] <video_game_console>
[FIND] <video_game_console>
[SWITCHON] <video_game_console>
[FIND] <video_game_controller>
[GRAB] <video_game_controller>
[PUTOBJBACK] <video_game_controller>
[SWITCHOFF] <video_game_console>
[FIND] <video_game_console>
[SWITCHON] <video_game_console>
[FIND] <video_game_controller>
[GRAB] <video_game_controller>


Instruction:
You serve as an AI task planner.
1. Your task is to create a plan to achieve a goal by converting it into a sequence of actions. Each action should follow the format "[verb] <target1> <target2>", where 'verb' represents the action, and 'target1' and 'target2' are optional arguments.
2. You must describe your plan in natural language at the beginning. After that, you should list all the actions together.
Ensure that you response can be parsed by Python json.loads.

Here is an example plan to achieve a goal for reference:
Scene_Objects:['water_glass', 'scissors', 'measuring_cup', 'freezer', 'food_butter', 'drawing', 'cpuscreen', 'wallshelf', 'hanger', 'floor', 'ceiling', 'character', 'food_cake', 'mat', 'mousepad', 'couch', 'pillow', 'dining_room', 'wall', 'nightstand', 'photoframe', 'food_food', 'check', 'television', 'water', 'kitchen_counter', 'cupboard', 'door', 'light', 'clothes_skirt']
Task:Drink
response:
{
    "thoughts": go to kitchen, find water glass and grab it, find fridge and open grab water and pour into it, then drink.,
    "actions": ['[WALK] <dining_room>', '[WALK] <water_glass>', '[FIND] <water_glass>', '[GRAB] <water_glass>', '[FIND] <freezer>', '[OPEN] <freezer>', '[WALK] <water>', '[FIND] <water>', '[GRAB] <water>', '[POUR] <water> <water_glass>', '[CLOSE] <freezer>', '[DRINK] <water_glass>']
}

Input:
Scene_Objects:['filing_cabinet', 'tablelamp', 'microwave', 'freezer', 'bathroom', 'milk', 'floor', 'bookshelf', 'closetdrawer', 'pillow', 'wall', 'wall_clock', 'bench', 'oven', 'toy', 'cutting_board', 'shelf', 'cup', 'standingmirror', 'bed', 'check', 'food_food', 'coffe_maker', 'after_shave', 'console', 'pencil', 'comb', 'sink', 'home_office', 'scrabble']
Task:Pick up toys
response:

Grab toys off floor.  Put it in a container.

[WALK] <bedroom>
[WALK] <toy>
[FIND] <toy>
[GRAB] <toy>
[WALK] <filing_cabinet>
[OPEN] <filing_cabinet>
[PUTBACK] <toy> <filing_cabinet>
[FIND] <toy>
[GRAB] <toy>
[WALK] <filing_cabinet>
[PUTBACK] <toy> <filing_cabinet>
[FIND] <toy>
[GRAB] <toy>
[WALK] <filing_cabinet>
[PUTBACK] <toy> <filing_cabinet>
[CLOSE] <filing_cabinet>


Instruction:
You serve as an AI task planner.
1. Your task is to create a plan to achieve a goal by converting it into a sequence of actions. Each action should follow the format "[verb] <target1> <target2>", where 'verb' represents the action, and 'target1' and 'target2' are optional arguments.
2. You must describe your plan in natural language at the beginning. After that, you should list all the actions together.
Ensure that you response can be parsed by Python json.loads.

Here is an example plan to achieve a goal for reference:
Scene_Objects:['tablelamp', 'food_salt', 'chair', 'walllamp', 'orchid', 'cpuscreen', 'floor', 'ceiling', 'remote_control', 'computer', 'button', 'tvstand', 'shower', 'window', 'mousepad', 'closetdrawer', 'couch', 'pillow', 'nightstand', 'wall', 'oven', 'coffee_table', 'novel', 'television', 'curtain', 'doorjamb', 'lighter', 'dresser', 'home_office', 'table']
Task:Change TV channel
response:
{
    "thoughts": Go to the living room, find the remote control on the coffee table, and change the TV channel.,
    "actions": ['[WALK] <home_office>', '[WALK] <coffee_table>', '[FIND] <coffee_table>', '[WALK] <coffee_table>', '[TURNTO] <coffee_table>', '[LOOKAT] <coffee_table>', '[FIND] <remote_control>', '[TOUCH] <remote_control>', '[GRAB] <remote_control>', '[FIND] <television>', '[TURNTO] <television>', '[POINTAT] <television>', '[FIND] <button>', '[TOUCH] <button>', '[PUSH] <button>']
}

Input:
Scene_Objects:['toilet', 'chair', 'bathroom', 'food_butter', 'orchid', 'cpuscreen', 'hanger', 'floor', 'ceiling', 'desk', 'keyboard', 'bookshelf', 'computer', 'shoe-shine_kit', 'shower', 'mousepad', 'closetdrawer', 'clothes_hat', 'wall', 'powersocket', 'cup', 'photoframe', 'novel', 'doorjamb', 'mouse', 'dresser', 'clothes_dress', 'light', 'clothes_skirt', 'vase']
Task:Sew
response:

Using  the sewing machine  to  fix  and make  clothes

[WALK] <bedroom>
[WALK] <dresser>
[OPEN] <dresser>
[FIND] <clothes_dress>
[GRAB] <clothes_dress>
[CLOSE] <dresser>
[FIND] <chair>
[SIT] <chair>


Instruction:
You serve as an AI task planner.
1. Your task is to create a plan to achieve a goal by converting it into a sequence of actions. Each action should follow the format "[verb] <target1> <target2>", where 'verb' represents the action, and 'target1' and 'target2' are optional arguments.
2. You must describe your plan in natural language at the beginning. After that, you should list all the actions together.
Ensure that you response can be parsed by Python json.loads.

Here is an example plan to achieve a goal for reference:
Scene_Objects:['microwave', 'ceilingfan', 'drawing', 'bills', 'bathroom_counter', 'floor', 'ceiling', 'bedroom', 'face', 'mail', 'table_cloth', 'faucet', 'food_jam', 'towel', 'dining_room', 'wall', 'face_soap', 'toy', 'photoframe', 'keys', 'water', 'rag', 'pencil', 'shoes', 'dresser', 'sink', 'bathroom_cabinet', 'home_office', 'colander', 'hands_both']
Task:Wash face
response:
{
    "thoughts": Turn on water faucet. Get rag wet. Get face soap out. Squirt face soap in hands and put it on face. Rub soap into face. Wash soap off of face. Dry face off on the hand towel. Hang out rag and hand towel.,
    "actions": ['[WALK] <bathroom>', '[WALK] <rag>', '[FIND] <rag>', '[GRAB] <rag>', '[WALK] <sink>', '[FIND] <faucet>', '[SWITCHON] <faucet>', '[PUTBACK] <rag> <sink>', '[GRAB] <rag>', '[FIND] <face_soap>', '[GRAB] <face_soap>', '[POUR] <face_soap> <rag>', '[PUTOBJBACK] <face_soap>', '[FIND] <face>', '[SCRUB] <face>', '[PUTBACK] <rag> <sink>', '[FIND] <water>', '[GRAB] <water>', '[FIND] <hands_both>', '[POUR] <water> <hands_both>', '[RINSE] <face>', '[WASH] <rag>', '[GRAB] <rag>', '[PUTOBJBACK] <rag>', '[SWITCHOFF] <faucet>', '[FIND] <towel>', '[GRAB] <towel>', '[WIPE] <face>', '[PUTOBJBACK] <towel>']
}

Input:
Scene_Objects:['mop', 'walllamp', 'food_butter', 'food_carrot', 'drawing', 'cpuscreen', 'food_egg', 'hanger', 'floor', 'ceiling', 'phone', 'desk', 'keyboard', 'computer', 'food_bacon', 'electric_shaver', 'mousepad', 'closetdrawer', 'wall', 'powersocket', 'photoframe', 'curtain', 'rag', 'mouse', 'shoes', 'dresser', 'hairdryer', 'bag', 'light', 'tooth_paste']
Task:Take off shoes
response:

Bend down to reach your feet. Shift balance to one leg. Grab the shoe of the foot of the other leg, it is best to use one hand to grip near the front, and one towards the heel. Pull the shoe down toward the ground while also pushing on the heel away from the body. Repeat with other shoe. Place shoes in a designated area.

[WALK] <bedroom>
[WALK] <shoes>
[FIND] <shoes>
[GRAB] <shoes>
[PULL] <shoes>
[WALK] <dresser>
[OPEN] <dresser>
[PUTIN] <shoes> <dresser>
[FIND] <shoes>
[GRAB] <shoes>
[PULL] <shoes>
[WALK] <dresser>
[PUTIN] <shoes> <dresser>
[CLOSE] <dresser>


Instruction:
You serve as an AI task planner.
1. Your task is to create a plan to achieve a goal by converting it into a sequence of actions. Each action should follow the format "[verb] <target1> <target2>", where 'verb' represents the action, and 'target1' and 'target2' are optional arguments.
2. You must describe your plan in natural language at the beginning. After that, you should list all the actions together.
Ensure that you response can be parsed by Python json.loads.

Here is an example plan to achieve a goal for reference:
Scene_Objects:['fork', 'drawing', 'cpuscreen', 'hanger', 'floor', 'ceiling', 'stamp', 'envelope', 'computer', 'stovefan', 'mat', 'ceilinglamp', 'window', 'closetdrawer', 'couch', 'pillow', 'dining_room', 'food_kiwi', 'wall', 'nightstand', 'powersocket', 'standingmirror', 'television', 'curtain', 'doorjamb', 'mouse', 'bag', 'home_office', 'table', 'soap']
Task:Relax on sofa
response:
{
    "thoughts": I walk to my living room and switch on the television, and lay on the sofa.,
    "actions": ['[WALK] <home_office>', '[WALK] <television>', '[FIND] <television>', '[SWITCHON] <television>', '[FIND] <couch>', '[LIE] <couch>']
}

Input:
Scene_Objects:['sheets', 'glue', 'tablelamp', 'cpuscreen', 'hanger', 'floor', 'ceiling', 'phone', 'desk', 'keyboard', 'purse', 'computer', 'clothes_jacket', 'toaster', 'stereo', 'mousepad', 'closetdrawer', 'couch', 'wall', 'wall_clock', 'powersocket', 'nightstand', 'bed', 'novel', 'mouse', 'shoes', 'dresser', 'clothes_dress', 'light', 'table']
Task:Get ready for day
response:

Grab shoes, purse etc and head out the door!

[WALK] <bedroom>
[WALK] <dresser>
[FIND] <dresser>
[OPEN] <dresser>
[FIND] <clothes_dress>
[GRAB] <clothes_dress>
[PUTON] <clothes_dress>
[FIND] <shoes>
[GRAB] <shoes>
[PUTON] <shoes>
[FIND] <purse>
[GRAB] <purse>
[CLOSE] <dresser>
[WALK] <home_office>


Instruction:
You serve as an AI task planner.
1. Your task is to create a plan to achieve a goal by converting it into a sequence of actions. Each action should follow the format "[verb] <target1> <target2>", where 'verb' represents the action, and 'target1' and 'target2' are optional arguments.
2. You must describe your plan in natural language at the beginning. After that, you should list all the actions together.
Ensure that you response can be parsed by Python json.loads.

Here is an example plan to achieve a goal for reference:
Scene_Objects:['band-aids', 'trashcan', 'wallshelf', 'clothes_underwear', 'desk', 'keyboard', 'mail', 'computer', 'tvstand', 'shower', 'window', 'clothes_socks', 'couch', 'food_peanut_butter', 'pillow', 'basket_for_clothes', 'keys', 'coffe_maker', 'television', 'food_donut', 'tray', 'rag', 'headset', 'clothes_scarf', 'bathtub', 'sink', 'light', 'dishwasher', 'soap', 'washing_machine']
Task:Wash clothes
response:
{
    "thoughts": Get dirty clothes out of basket for clothes in bedroom, carry dirty clothes to laundry room, place dirty clothes in washing machine, add laundry detergent to washing machine, turn washing machine on, set type of wash, start washing machine,
    "actions": ['[WALK] <bedroom>', '[WALK] <basket_for_clothes>', '[FIND] <basket_for_clothes>', '[OPEN] <basket_for_clothes>', '[GRAB] <basket_for_clothes>', '[WALK] <bathroom>', '[WALK] <washing_machine>', '[FIND] <washing_machine>', '[OPEN] <washing_machine>', '[PUTBACK] <basket_for_clothes> <washing_machine>', '[FIND] <soap>', '[GRAB] <soap>', '[PUTBACK] <soap> <washing_machine>', '[FIND] <washing_machine>', '[CLOSE] <washing_machine>', '[SWITCHON] <washing_machine>']
}

Input:
Scene_Objects:['knife', 'cpuscreen', 'hanger', 'floor', 'ceiling', 'folder', 'desk', 'keyboard', 'computer', 'mat', 'stereo', 'mousepad', 'closetdrawer', 'clothes_pants', 'wall', 'powersocket', 'cup', 'newspaper', 'novel', 'tray', 'mouse', 'kitchen_counter', 'dresser', 'bathtub', 'spoon', 'light', 'soap', 'board_game', 'clothes_shirt', 'scrabble']
Task:Get dressed
response:

Pick out the clothes you are going to wear and put them on your body

[WALK] <bedroom>
[WALK] <dresser>
[OPEN] <dresser>
[FIND] <clothes_pants>
[GRAB] <clothes_pants>
[PUTON] <clothes_pants>
[FIND] <clothes_shirt>
[GRAB] <clothes_shirt>
[PUTON] <clothes_shirt>
[CLOSE] <dresser>


Instruction:
You serve as an AI task planner.
1. Your task is to create a plan to achieve a goal by converting it into a sequence of actions. Each action should follow the format "[verb] <target1> <target2>", where 'verb' represents the action, and 'target1' and 'target2' are optional arguments.
2. You must describe your plan in natural language at the beginning. After that, you should list all the actions together.
Ensure that you response can be parsed by Python json.loads.

Here is an example plan to achieve a goal for reference:
Scene_Objects:['sponge', 'tablelamp', 'microwave', 'chair', 'trashcan', 'ceilingfan', 'drawing', 'orchid', 'cpuscreen', 'floor', 'ceiling', 'phone', 'desk', 'keyboard', 'bookshelf', 'computer', 'ceilinglamp', 'balanceball', 'mousepad', 'wall', 'nightstand', 'bench', 'cup', 'doorjamb', 'mouse', 'address_book', 'hairbrush', 'hairdryer', 'light', 'creditcard']
Task:Work
response:
{
    "thoughts": Walk to home office. Walk to computer. Switch on computer. Open the address book.,
    "actions": ['[WALK] <home_office>', '[WALK] <computer>', '[SWITCHON] <computer>', '[FIND] <address_book>']
}

Input:
Scene_Objects:['juice', 'blender', 'beer', 'microwave', 'freezer', 'walllamp', 'detergent', 'floor', 'ceiling', 'character', 'stovefan', 'faucet', 'couch', 'clothes_hat', 'food_orange', 'broom', 'wall', 'oven', 'cutting_board', 'shelf', 'food_cheese', 'bed', 'coffe_maker', 'food_food', 'tray', 'after_shave', 'lighter', 'kitchen_counter', 'vase', 'coffee']
Task:Eat cheese
response:

[WALK] <dining_room>
[WALK] <freezer>
[OPEN] <freezer>
[FIND] <food_cheese>
[GRAB] <food_cheese>
[EAT] <food_cheese>


Instruction:
You serve as an AI task planner.
1. Your task is to create a plan to achieve a goal by converting it into a sequence of actions. Each action should follow the format "[verb] <target1> <target2>", where 'verb' represents the action, and 'target1' and 'target2' are optional arguments.
2. You must describe your plan in natural language at the beginning. After that, you should list all the actions together.
Ensure that you response can be parsed by Python json.loads.

Here is an example plan to achieve a goal for reference:
Scene_Objects:['filing_cabinet', 'tablelamp', 'tea', 'chair', 'dog', 'freezer', 'walllamp', 'drawing', 'bathroom_counter', 'floor', 'ceiling', 'desk', 'bookshelf', 'computer', 'mat', 'ceilinglamp', 'couch', 'pillow', 'wall', 'nightstand', 'powersocket', 'pasta', 'light_bulb', 'clothes_gloves', 'television', 'curtain', 'doorjamb', 'conditioner', 'door', 'light']
Task:Relax on sofa
response:
{
    "thoughts": I walk into the living room and turn on the light. I walk to the couch then sit on the couch.,
    "actions": ['[WALK] <home_office>', '[WALK] <light>', '[FIND] <light>', '[SWITCHON] <light>', '[WALK] <couch>', '[SIT] <couch>']
}

Input:
Scene_Objects:['spectacles', 'microwave', 'chair', 'dog', 'walllamp', 'drawing', 'cpuscreen', 'hanger', 'floor', 'ceiling', 'phone', 'desk', 'bookshelf', 'keyboard', 'computer', 'laptop', 'mat', 'mousepad', 'closetdrawer', 'couch', 'wall', 'powersocket', 'coffe_maker', 'wine', 'doorjamb', 'kettle', 'mouse', 'pencil', 'dresser', 'light']
Task:Work
response:

I walk in. Turn on the light. Set in my chair. Turn on lap top. And start to work.

[WALK] <home_office>
[WALK] <light>
[FIND] <light>
[SWITCHON] <light>
[FIND] <chair>
[SIT] <chair>
[FIND] <laptop>
[GRAB] <laptop>
[SWITCHON] <laptop>


Instruction:
You serve as an AI task planner.
1. Your task is to create a plan to achieve a goal by converting it into a sequence of actions. Each action should follow the format "[verb] <target1> <target2>", where 'verb' represents the action, and 'target1' and 'target2' are optional arguments.
2. You must describe your plan in natural language at the beginning. After that, you should list all the actions together.
Ensure that you response can be parsed by Python json.loads.

Here is an example plan to achieve a goal for reference:
Scene_Objects:['sheets', 'filing_cabinet', 'mop', 'bathroom', 'dough', 'knifeblock', 'hanger', 'keyboard', 'alcohol', 'toaster', 'shower', 'foundation', 'couch', 'bowl', 'wall', 'pasta', 'basket_for_clothes', 'check', 'television', 'razor', 'tray', 'doorjamb', 'chessboard', 'dishrack', 'hairbrush', 'napkin', 'bathroom_cabinet', 'light', 'dishwasher', 'table']
Task:Pick up phone
response:
{
    "thoughts": go to living room, find phone, pick up phone,
    "actions": ['[WALK] <home_office>', '[WALK] <phone>', '[FIND] <phone>', '[GRAB] <phone>']
}

Input:
Scene_Objects:['sheets', 'freezer', 'nail_polish', 'woman', 'bathroom_counter', 'floor', 'shampoo', 'man', 'keyboard', 'purse', 'stovefan', 'mat', 'window', 'couch', 'pillow', 'dining_room', 'food_kiwi', 'wall', 'wall_clock', 'bench', 'shelf', 'standingmirror', 'check', 'television', 'curtain', 'doorjamb', 'pencil', 'bag', 'table', 'soap']
Task:Hang with friends
response:

[WALK] <home_office>
[WALK] <man>
[FIND] <man>
[TURNTO] <man>
[LOOKAT] <man>
[GREET] <man>
[FIND] <woman>
[TURNTO] <woman>
[LOOKAT] <woman>
[GREET] <woman>
[WALK] <couch>
[SIT] <couch>
[TURNTO] <man>
[LOOKAT] <man>
[GREET] <man>
[TURNTO] <woman>
[LOOKAT] <woman>
[GREET] <woman>


Instruction:
You serve as an AI task planner.
1. Your task is to create a plan to achieve a goal by converting it into a sequence of actions. Each action should follow the format "[verb] <target1> <target2>", where 'verb' represents the action, and 'target1' and 'target2' are optional arguments.
2. You must describe your plan in natural language at the beginning. After that, you should list all the actions together.
Ensure that you response can be parsed by Python json.loads.

Here is an example plan to achieve a goal for reference:
Scene_Objects:['dry_pasta', 'microwave', 'walllamp', 'bathroom', 'trashcan', 'milk', 'floor', 'ceiling', 'desk', 'keyboard', 'button', 'mop_bucket', 'toaster', 'stereo', 'window', 'wall', 'powersocket', 'bench', 'newspaper', 'coffe_maker', 'tray', 'curtain', 'food_sugar', 'kitchen_counter', 'vacuum_cleaner', 'cupboard', 'coffee_cup', 'dishwasher', 'light', 'clothes_shirt']
Task:Make coffee
response:
{
    "thoughts": walk to kitchen, look at the coffee maker, open the coffee maker, find milk, suger and water, mix that all, put into coffee maker, switch on the coffee maker, wait for few mins, push the coffee button in coffee maker, we get coffee in coffee cup, drink coffee,
    "actions": ['[WALK] <dining_room>', '[WALK] <coffe_maker>', '[FIND] <coffe_maker>', '[TURNTO] <coffe_maker>', '[LOOKAT] <coffe_maker>', '[OPEN] <coffe_maker>', '[FIND] <milk>', '[GRAB] <milk>', '[PUTBACK] <milk> <coffe_maker>', '[FIND] <food_sugar>', '[FIND] <coffee_cup>', '[GRAB] <coffee_cup>', '[PUTBACK] <coffee_cup> <coffe_maker>', '[SWITCHON] <coffe_maker>', '[FIND] <button>', '[PUSH] <button>', '[GRAB] <coffee_cup>', '[DRINK] <coffee_cup>']
}

Input:
Scene_Objects:['pot', 'tablelamp', 'walllamp', 'woman', 'drawing', 'phone', 'desk', 'man', 'toaster', 'laptop', 'mat', 'shower', 'electric_shaver', 'oil', 'form', 'pillow', 'dining_room', 'oven', 'shelf', 'bed', 'standingmirror', 'toothbrush_holder', 'tray', 'curtain', 'doorjamb', 'mouse', 'door', 'bathroom_cabinet', 'tooth_paste', 'scrabble']
Task:Greet guests
response:

Answer the door. Smile and give a warm hello, or other appropriate greeting. With newcomers to your home, offer your hand to be shook. With old friends it is appropriate to hug, or kiss one another on the cheek.

[WALK] <home_office>
[WALK] <man>
[FIND] <man>
[GREET] <man>
[FIND] <woman>
[GREET] <woman>


Instruction:
You serve as an AI task planner.
1. Your task is to create a plan to achieve a goal by converting it into a sequence of actions. Each action should follow the format "[verb] <target1> <target2>", where 'verb' represents the action, and 'target1' and 'target2' are optional arguments.
2. You must describe your plan in natural language at the beginning. After that, you should list all the actions together.
Ensure that you response can be parsed by Python json.loads.

Here is an example plan to achieve a goal for reference:
Scene_Objects:['microwave', 'nail_polish', 'drawing', 'wallshelf', 'hanger', 'floor', 'ceiling', 'shampoo', 'bedroom', 'tea_bag', 'laptop', 'tvstand', 'clothes_socks', 'closetdrawer', 'couch', 'clothes_hat', 'wall', 'nightstand', 'powersocket', 'photoframe', 'coffe_maker', 'check', 'television', 'doorjamb', 'towel_rack', 'cards', 'dresser', 'door', 'home_office', 'light']
Task:Turn on light
response:
{
    "thoughts": I walk into the dining room and turn on the lights,
    "actions": ['[WALK] <dining_room>', '[WALK] <light>', '[FIND] <light>', '[SWITCHON] <light>']
}

Input:
Scene_Objects:['sheets', 'tablelamp', 'dough', 'drawing', 'cpuscreen', 'hanger', 'floor', 'ceiling', 'desk', 'keyboard', 'computer', 'mat', 'window', 'mousepad', 'closetdrawer', 'pillow', 'wall', 'nightstand', 'powersocket', 'bed', 'novel', 'check', 'curtain', 'mouse', 'pencil', 'dresser', 'light', 'table', 'vase', 'shoe_rack']
Task:Read book
response:

[WALK] <bedroom>
[WALK] <dresser>
[OPEN] <dresser>
[FIND] <novel>
[GRAB] <novel>
[FIND] <bed>
[SIT] <bed>
[READ] <novel>


Instruction:
You serve as an AI task planner.
1. Your task is to create a plan to achieve a goal by converting it into a sequence of actions. Each action should follow the format "[verb] <target1> <target2>", where 'verb' represents the action, and 'target1' and 'target2' are optional arguments.
2. You must describe your plan in natural language at the beginning. After that, you should list all the actions together.
Ensure that you response can be parsed by Python json.loads.

Here is an example plan to achieve a goal for reference:
Scene_Objects:['chair', 'walllamp', 'blow_dryer', 'knifeblock', 'drawing', 'cpuscreen', 'bathroom_counter', 'floor', 'ceiling', 'folder', 'desk', 'food_cake', 'stovefan', 'toaster', 'deck_of_cards', 'faucet', 'candle', 'pillow', 'dining_room', 'oven', 'photoframe', 'check', 'food_food', 'television', 'bathroom_cabinet', 'table', 'dishwasher', 'soap', 'board_game', 'clothes_shirt']
Task:Pet cat
response:
{
    "thoughts": Walk to living room. Find cat. Walk to cat. Pull cat.,
    "actions": ['[WALK] <home_office>', '[WALK] <cat>', '[FIND] <cat>', '[WALK] <cat>', '[PULL] <cat>']
}

Input:
Scene_Objects:['sheets', 'spectacles', 'filing_cabinet', 'food_salt', 'walllamp', 'drawing', 'bathroom_counter', 'floor', 'character', 'shower', 'stereo', 'microphone', 'wall', 'toy', 'cutting_board', 'cup', 'novel', 'food_food', 'check', 'food_onion', 'coffee_pot', 'console', 'shaving_cream', 'towel_rack', 'shoes', 'cd', 'hairbrush', 'maindoor', 'soap', 'coffee']
Task:Read
response:

[WALK] <home_office>
[WALK] <filing_cabinet>
[OPEN] <filing_cabinet>
[FIND] <novel>
[GRAB] <novel>
[CLOSE] <filing_cabinet>
[READ] <novel>


Instruction:
You serve as an AI task planner.
1. Your task is to create a plan to achieve a goal by converting it into a sequence of actions. Each action should follow the format "[verb] <target1> <target2>", where 'verb' represents the action, and 'target1' and 'target2' are optional arguments.
2. You must describe your plan in natural language at the beginning. After that, you should list all the actions together.
Ensure that you response can be parsed by Python json.loads.

Here is an example plan to achieve a goal for reference:
Scene_Objects:['sheets', 'glue', 'toilet', 'chair', 'bathroom', 'drawing', 'longboard', 'floor', 'ceiling', 'food_cake', 'mat', 'ceilinglamp', 'shower', 'deck_of_cards', 'balanceball', 'shoe-shine_kit', 'tvstand', 'candle', 'food_kiwi', 'wall', 'nightstand', 'powersocket', 'bench', 'food_cheese', 'novel', 'coffe_maker', 'curtain', 'towel_rack', 'home_office', 'dishwasher']
Task:Take shower
response:
{
    "thoughts": Walk to the bathroom and wash with the shower.,
    "actions": ['[WALK] <bathroom>', '[WALK] <shower>', '[FIND] <shower>', '[WASH] <shower>']
}

Input:
Scene_Objects:['chair', 'drawing', 'hanger', 'floor', 'ceiling', 'character', 'keyboard', 'tvstand', 'shower', 'closetdrawer', 'wall', 'wall_clock', 'oven', 'cup', 'standingmirror', 'check', 'television', 'centerpiece', 'console', 'mouse', 'vacuum_cleaner', 'shoes', 'comb', 'dresser', 'hairbrush', 'sink', 'bag', 'napkin', 'bathroom_cabinet', 'vase']
Task:vacuum carpet
response:

I bring my vacuum cleaner into the living room.  I plug it into the wall.  I press the on switch on the vacuum cleaner.  I push the vacuum cleaner back and forth over the length and width of the carpet until I have vacuumed the entire carpet.  I turn the vacuum cleaner off.  I take the vacuum cleaner back to the hall closet.

[WALK] <home_office>
[WALK] <dresser>
[OPEN] <dresser>
[FIND] <vacuum_cleaner>
[GRAB] <vacuum_cleaner>
[PULL] <vacuum_cleaner>
[PLUGIN] <vacuum_cleaner>
[SWITCHON] <vacuum_cleaner>
[PULL] <vacuum_cleaner>
[PUSH] <vacuum_cleaner>
[PULL] <vacuum_cleaner>
[PUSH] <vacuum_cleaner>
[PULL] <vacuum_cleaner>
[PUSH] <vacuum_cleaner>
[SWITCHOFF] <vacuum_cleaner>
[PLUGOUT] <vacuum_cleaner>
[WALK] <dresser>
[PUTIN] <vacuum_cleaner> <dresser>
[CLOSE] <dresser>


Instruction:
You serve as an AI task planner.
1. Your task is to create a plan to achieve a goal by converting it into a sequence of actions. Each action should follow the format "[verb] <target1> <target2>", where 'verb' represents the action, and 'target1' and 'target2' are optional arguments.
2. You must describe your plan in natural language at the beginning. After that, you should list all the actions together.
Ensure that you response can be parsed by Python json.loads.

Here is an example plan to achieve a goal for reference:
Scene_Objects:['filing_cabinet', 'toilet', 'bathroom', 'drawing', 'bathroom_counter', 'floor', 'ceiling', 'character', 'keyboard', 'computer', 'stovefan', 'faucet', 'window', 'mousepad', 'closetdrawer', 'couch', 'towel', 'wall', 'nightstand', 'curtain', 'towel_rack', 'mouse', 'coffee_pot', 'dresser', 'sink', 'bathtub', 'bathroom_cabinet', 'home_office', 'soap', 'hands_both']
Task:Wash hands
response:
{
    "thoughts": I go to the bathroom and locate the sink. I turn the faucet so that water is running, and rinse my hands briefly. Then I grab the soap and squeeze some onto my hands. I spend a few minutes rubbing my hands together, then I rinse them again. Finally, I turn the faucet off and wipe my hands on a towel.,
    "actions": ['[WALK] <bathroom>', '[WALK] <sink>', '[FIND] <sink>', '[TURNTO] <sink>', '[FIND] <faucet>', '[SWITCHON] <faucet>', '[FIND] <hands_both>', '[RINSE] <hands_both>', '[FIND] <soap>', '[GRAB] <soap>', '[SQUEEZE] <soap>', '[WASH] <hands_both>', '[RINSE] <hands_both>', '[SWITCHOFF] <faucet>', '[FIND] <towel>', '[GRAB] <towel>', '[WIPE] <hands_both>']
}

Input:
Scene_Objects:['food_bread', 'tablelamp', 'blender', 'tea', 'chair', 'freezer', 'drawing', 'orchid', 'hanger', 'floor', 'shampoo', 'stamp', 'bedroom', 'desk', 'computer', 'mat', 'stereo', 'mousepad', 'food_jam', 'dining_room', 'wall', 'wall_clock', 'bench', 'photoframe', 'food_food', 'dresser', 'napkin', 'home_office', 'table', 'spoon']
Task:Eat dinner
response:

In our dining room, my family eats dinner. Once the food has been prepared, we gather at the dining room table and prepare to eat.

[WALK] <dining_room>
[WALK] <food_food>
[FIND] <food_food>
[GRAB] <food_food>
[WALK] <dining_room>
[WALK]

[PUTBACK] <food_food>

[WALK] <dining_room>
[WALK] <food_food>
[FIND] <food_food>
[GRAB] <food_food>
[WALK] <dining_room>
[WALK]

[PUTBACK] <food_food>

[WALK] <chair>
[PULL] <chair>
[SIT] <chair>
[TURNTO] <food_food>
[LOOKAT] <food_food>
[TURNTO] <food_food>
[LOOKAT] <food_food>


Instruction:
You serve as an AI task planner.
1. Your task is to create a plan to achieve a goal by converting it into a sequence of actions. Each action should follow the format "[verb] <target1> <target2>", where 'verb' represents the action, and 'target1' and 'target2' are optional arguments.
2. You must describe your plan in natural language at the beginning. After that, you should list all the actions together.
Ensure that you response can be parsed by Python json.loads.

Here is an example plan to achieve a goal for reference:
Scene_Objects:['chair', 'walllamp', 'bathroom', 'orchid', 'cpuscreen', 'floor', 'ceiling', 'desk', 'keyboard', 'computer', 'food_bacon', 'bookmark', 'mat', 'ceilinglamp', 'tvstand', 'deck_of_cards', 'mousepad', 'closetdrawer', 'pillow', 'wall', 'nightstand', 'cup', 'television', 'doorjamb', 'mouse', 'kitchen_counter', 'vacuum_cleaner', 'door', 'light', 'table']
Task:Vacuum
response:
{
    "thoughts": Keep my keyboard vacuumed and free of debris.,
    "actions": ['[WALK] <home_office>', '[WALK] <computer>', '[FIND] <vacuum_cleaner>', '[SWITCHON] <vacuum_cleaner>', '[SWITCHOFF] <vacuum_cleaner>']
}

Input:
Scene_Objects:['chair', 'walllamp', 'bathroom', 'detergent', 'dough', 'drawing', 'cpuscreen', 'floor', 'ceiling', 'character', 'desk', 'keyboard', 'thread', 'computer', 'ceilinglamp', 'mousepad', 'closetdrawer', 'wall', 'powersocket', 'photoframe', 'toilet_paper', 'television', 'razor', 'coin', 'doorjamb', 'mouse', 'kitchen_counter', 'dresser', 'light', 'table']
Task:Turn on computer
response:

[WALK] <home_office>
[WALK] <computer>
[SWITCHON] <computer>


Instruction:
You serve as an AI task planner.
1. Your task is to create a plan to achieve a goal by converting it into a sequence of actions. Each action should follow the format "[verb] <target1> <target2>", where 'verb' represents the action, and 'target1' and 'target2' are optional arguments.
2. You must describe your plan in natural language at the beginning. After that, you should list all the actions together.
Ensure that you response can be parsed by Python json.loads.

Here is an example plan to achieve a goal for reference:
Scene_Objects:['filing_cabinet', 'walllamp', 'cat', 'drawing', 'orchid', 'wallshelf', 'hanger', 'floor', 'ceiling', 'bookshelf', 'keyboard', 'toaster', 'mat', 'tvstand', 'ceilinglamp', 'faucet', 'window', 'plate', 'couch', 'pillow', 'wall', 'newspaper', 'coffe_maker', 'television', 'curtain', 'doorjamb', 'kitchen_counter', 'bathtub', 'light', 'table']
Task:Pet cat
response:
{
    "thoughts": My cat looks like it wants attention, so I will go pet it on the couch.,
    "actions": ['[WALK] <home_office>', '[WALK] <light>', '[FIND] <light>', '[SWITCHON] <light>', '[FIND] <cat>', '[WALK] <couch>', '[SIT] <couch>', '[TURNTO] <cat>', '[TOUCH] <cat>']
}

Input:
Scene_Objects:['filing_cabinet', 'blender', 'band-aids', 'freezer', 'orchid', 'cpuscreen', 'floor', 'bookshelf', 'envelope', 'toaster', 'stovefan', 'plate', 'shower', 'faucet', 'foundation', 'oil', 'mousepad', 'food_jam', 'microphone', 'dining_room', 'bench', 'oven', 'toy', 'box', 'food_food', 'food_onion', 'diary', 'kitchen_counter', 'cupboard', 'colander']
Task:Get out dish
response:

[WALK] <dining_room>
[WALK] <cupboard>
[OPEN] <cupboard>
[FIND] <plate>
[GRAB] <plate>
[CLOSE] <cupboard>


Instruction:
You serve as an AI task planner.
1. Your task is to create a plan to achieve a goal by converting it into a sequence of actions. Each action should follow the format "[verb] <target1> <target2>", where 'verb' represents the action, and 'target1' and 'target2' are optional arguments.
2. You must describe your plan in natural language at the beginning. After that, you should list all the actions together.
Ensure that you response can be parsed by Python json.loads.

Here is an example plan to achieve a goal for reference:
Scene_Objects:['tablelamp', 'chair', 'walllamp', 'drawing', 'orchid', 'cpuscreen', 'wallshelf', 'hanger', 'floor', 'ceiling', 'phone', 'desk', 'keyboard', 'computer', 'mat', 'ceilinglamp', 'tvstand', 'mousepad', 'couch', 'pillow', 'dining_room', 'wall', 'nightstand', 'oven', 'television', 'doorjamb', 'mouse', 'dresser', 'door', 'soap']
Task:Work
response:
{
    "thoughts": I go to my home office, sit on the chair and turn on the computer. I open my email account to look for all the information I need.I pull up my online task on the computer to look at what the assigned task is.,
    "actions": ['[WALK] <home_office>', '[WALK] <chair>', '[FIND] <chair>', '[SIT] <chair>', '[FIND] <computer>', '[SWITCHON] <computer>', '[TURNTO] <computer>', '[LOOKAT] <computer>', '[FIND] <mouse>', '[GRAB] <mouse>', '[FIND] <keyboard>', '[TYPE] <keyboard>', '[TURNTO] <computer>', '[LOOKAT] <computer>']
}

Input:
Scene_Objects:['fork', 'sheets', 'food_salt', 'tea', 'blow_dryer', 'wallshelf', 'ceiling', 'character', 'food_cake', 'computer', 'tvstand', 'window', 'mousepad', 'cutting_board', 'basket_for_clothes', 'cup', 'newspaper', 'light_bulb', 'novel', 'photoframe', 'coin', 'food_donut', 'rag', 'cards', 'kitchen_counter', 'vacuum_cleaner', 'pajamas', 'maindoor', 'bag', 'creditcard']
Task:Clean
response:

[WALK] <home_office>
[WALK] <vacuum_cleaner>
[FIND] <vacuum_cleaner>
[GRAB] <vacuum_cleaner>
[SWITCHON] <vacuum_cleaner>
[SWITCHOFF] <vacuum_cleaner>


Instruction:
You serve as an AI task planner.
1. Your task is to create a plan to achieve a goal by converting it into a sequence of actions. Each action should follow the format "[verb] <target1> <target2>", where 'verb' represents the action, and 'target1' and 'target2' are optional arguments.
2. You must describe your plan in natural language at the beginning. After that, you should list all the actions together.
Ensure that you response can be parsed by Python json.loads.

Here is an example plan to achieve a goal for reference:
Scene_Objects:['tablelamp', 'microwave', 'toilet', 'walllamp', 'trashcan', 'drawing', 'cpuscreen', 'wallshelf', 'floor', 'ceiling', 'keyboard', 'mat', 'tvstand', 'ceilinglamp', 'faucet', 'window', 'mousepad', 'closetdrawer', 'couch', 'pillow', 'dining_room', 'food_kiwi', 'wall', 'light_bulb', 'novel', 'television', 'curtain', 'cupboard', 'bathtub', 'table']
Task:Read book
response:
{
    "thoughts": I go to the living room, take a book from the shelf, sit in the sofa and read the book,
    "actions": ['[WALK] <home_office>', '[WALK] <novel>', '[FIND] <novel>', '[GRAB] <novel>', '[FIND] <couch>', '[SIT] <couch>', '[READ] <novel>']
}

Input:
Scene_Objects:['sheets', 'fork', 'scissors', 'food_salt', 'dog', 'milk', 'drawing', 'needle', 'hanger', 'bedroom', 'keyboard', 'bookshelf', 'stovefan', 'tvstand', 'closetdrawer', 'wall_clock', 'oven', 'toy', 'photoframe', 'novel', 'toilet_paper', 'food_food', 'check', 'food_onion', 'kitchen_counter', 'hairdryer', 'bathtub', 'vase', 'instrument_violin', 'creditcard']
Task:Read book
response:

Go to the book shelf, get a book, open the book and read the book.

[WALK] <home_office>
[WALK] <novel>
[FIND] <novel>
[GRAB] <novel>
[READ] <novel>


Instruction:
You serve as an AI task planner.
1. Your task is to create a plan to achieve a goal by converting it into a sequence of actions. Each action should follow the format "[verb] <target1> <target2>", where 'verb' represents the action, and 'target1' and 'target2' are optional arguments.
2. You must describe your plan in natural language at the beginning. After that, you should list all the actions together.
Ensure that you response can be parsed by Python json.loads.

Here is an example plan to achieve a goal for reference:
Scene_Objects:['filing_cabinet', 'walllamp', 'bathroom', 'drawing', 'orchid', 'hanger', 'floor', 'ceiling', 'desk', 'ceilinglamp', 'tvstand', 'mat', 'window', 'couch', 'clothes_hat', 'pillow', 'dining_room', 'wall', 'powersocket', 'clothes_gloves', 'television', 'razor', 'curtain', 'doorjamb', 'console', 'mouse', 'door', 'bag', 'table', 'dishwasher']
Task:Change TV channel
response:
{
    "thoughts": I walk in living room. I find TV remote. I grab TV remote. I sit on sofa. I switch on TV. I switch channel.,
    "actions": ['[WALK] <home_office>', '[WALK] <remote_control>', '[FIND] <remote_control>', '[GRAB] <remote_control>', '[WALK] <couch>', '[SIT] <couch>', '[FIND] <television>', '[SWITCHON] <television>', '[TURNTO] <remote_control>', '[LOOKAT] <remote_control>', '[PUSH] <remote_control>']
}

Input:
Scene_Objects:['sheets', 'pot', 'filing_cabinet', 'walllamp', 'drawing', 'cpuscreen', 'floor', 'phone', 'button', 'mat', 'stereo', 'window', 'homework', 'foundation', 'couch', 'pillow', 'wall', 'toy', 'cup', 'light_bulb', 'television', 'razor', 'curtain', 'after_shave', 'doorjamb', 'rag', 'coffee_pot', 'laundry_detergent', 'bathtub', 'table']
Task:Arrange furniture
response:

[WALK] <home_office>
[WALK] <coffee_table>
[PUSH] <coffee_table>
[WALK] <couch>
[PUSH] <couch>
[WALK] <couch>
[PUSH] <couch>
[WALK] <filing_cabinet>
[PUSH] <filing_cabinet>