metadata
library_name: hivex
original_train_name: WildfireResourceManagement_difficulty_8_task_2_run_id_2_train
tags:
- hivex
- hivex-wildfire-resource-management
- reinforcement-learning
- multi-agent-reinforcement-learning
model-index:
- name: hivex-WRM-PPO-baseline-task-2-difficulty-8
results:
- task:
type: sub-task
name: distribute_all
task-id: 2
difficulty-id: 8
dataset:
name: hivex-wildfire-resource-management
type: hivex-wildfire-resource-management
metrics:
- type: cumulative_reward
value: 957.9527984619141 +/- 552.1106666076138
name: Cumulative Reward
verified: true
- type: collective_performance
value: 58.90835800170898 +/- 29.141080333691164
name: Collective Performance
verified: true
- type: individual_performance
value: 32.591598701477054 +/- 18.37336995311841
name: Individual Performance
verified: true
- type: reward_for_moving_resources_to_neighbours
value: 848.1016296386719 +/- 473.59086332949374
name: Reward for Moving Resources to Neighbours
verified: true
- type: reward_for_moving_resources_to_self
value: 0.46286826878786086 +/- 0.5511730499835104
name: Reward for Moving Resources to Self
verified: true
This model serves as the baseline for the Wildfire Resource Management environment, trained and tested on task 2 with difficulty 8 using the Proximal Policy Optimization (PPO) algorithm.
Environment: Wildfire Resource Management
Task: 2
Difficulty: 8
Algorithm: PPO
Episode Length: 500
Training max_steps: 450000
Testing max_steps: 45000
Train & Test Scripts
Download the Environment