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| # to run Python-ACT-R in Notebook, we need to install the package if not done already: | |
| #from python_actr import * | |
| # Using the code above, if python_actr is not installed, it first install python_actr | |
| # then imports its modules: from python_actr import * | |
| # so no needs to import the following modules one by one, but you can use them instead | |
| # by uncommenting one by one, when needed, instead of importing everything at once: | |
| import python_actr | |
| from python_actr import log | |
| from python_actr import ACTR | |
| from python_actr import Model | |
| from python_actr import Buffer | |
| from python_actr import Memory | |
| from python_actr import DMSpreading | |
| from python_actr import log_everything | |
| #logev=log_everything(html=False) | |
| class MyEnv(Model): | |
| pass | |
| class MyAgent(ACTR): | |
| production_time = 0.05 | |
| production_sd = 0.01 | |
| production_threshold = -20 | |
| goal = Buffer() # Creating the goal buffer for the agent | |
| def init(): # this rule fires when the agent is instantiated. | |
| goal.set("sandwich bread") # set goal buffer to direct program flow | |
| def bread_bottom(goal="sandwich bread"): # if goal="sandwich bread" , fire rule | |
| print("I have a piece of bread2") | |
| #logging.warning("I have a piece of bread") | |
| goal.set("stop") # set goal buffer to direct program flow | |
| def stop_production(goal="stop"): | |
| self.stop() # stop the agent | |
| #tim = MyAgent() | |
| #subway=MyEnv() | |
| #subway.agent=tim | |
| #logev(subway) | |
| #subway.run() |