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CognitiveScience
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d31e9b7
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Parent(s):
efae330
Create dcogsphere.py
Browse files- dcogsphere.py +38 -0
dcogsphere.py
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# to run Python-ACT-R in Notebook, we need to install the package if not done already:
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from python_actr import *
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# Using the code above, if python_actr is not installed, it first install python_actr
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# then imports its modules: from python_actr import *
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# so no needs to import the following modules one by one, but you can use them instead
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# by uncommenting one by one, when needed, instead of importing everything at once:
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#import python_actr
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#from python_actr import log
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#from python_actr import ACTR
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#from python_actr import Model
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#from python_actr import Buffer
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#from python_actr import Memory
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#from python_actr import DMSpreading
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#from python_actr import log_everything
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class MyEnv(Model):
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pass
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class MyAgent(ACTR):
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production_time = 0.05
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production_sd = 0.01
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production_threshold = -20
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goal = Buffer() # Creating the goal buffer for the agent
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def init(): # this rule fires when the agent is instantiated.
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goal.set("sandwich bread") # set goal buffer to direct program flow
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def bread_bottom(goal="sandwich bread"): # if goal="sandwich bread" , fire rule
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print("I have a piece of bread2")
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#logging.warning("I have a piece of bread")
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goal.set("stop") # set goal buffer to direct program flow
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def stop_production(goal="stop"):
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self.stop() # stop the agent
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tim = MyAgent()
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subway=MyEnv()
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subway.agent=tim
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log_everything(subway)
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subway.run()
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