def test_TableDrivenAgent():
loc_A, loc_B = (0, 0), (1, 0)
# table defining all the possible states of the agent
table = {((loc_A, 'Clean'),): 'Right',
((loc_A, 'Dirty'),): 'Suck',
((loc_B, 'Clean'),): 'Left',
((loc_B, 'Dirty'),): 'Suck',
((loc_A, 'Dirty'), (loc_A, 'Clean')): 'Right',
((loc_A, 'Clean'), (loc_B, 'Dirty')): 'Suck',
((loc_B, 'Clean'), (loc_A, 'Dirty')): 'Suck',
((loc_B, 'Dirty'), (loc_B, 'Clean')): 'Left',
((loc_A, 'Dirty'), (loc_A, 'Clean'), (loc_B, 'Dirty')): 'Suck',
((loc_B, 'Dirty'), (loc_B, 'Clean'), (loc_A, 'Dirty')): 'Suck'
}
# create an program and then an object of the TableDrivenAgent
program = TableDrivenAgentProgram(table)
agent = Agent(program)
# create an object of TrivialVacuumEnvironment
environment = TrivialVacuumEnvironment()
# initializing some environment status
environment.status = {loc_A:'Dirty', loc_B:'Dirty'}
# add agent to the environment
environment.add_thing(agent)
# run the environment by single step everytime to check how environment evolves using TableDrivenAgentProgram
environment.run(steps = 1)
assert environment.status == {(1,0): 'Clean', (0,0): 'Dirty'}
environment.run(steps = 1)
assert environment.status == {(1,0): 'Clean', (0,0): 'Dirty'}
environment.run(steps = 1)
assert environment.status == {(1,0): 'Clean', (0,0): 'Clean'}
def test_TableDrivenAgent():
loc_A, loc_B = (0, 0), (1, 0)
# table defining all the possible states of the agent
table = {
((loc_A, 'Clean'), ): 'Right',
((loc_A, 'Dirty'), ): 'Suck',
((loc_B, 'Clean'), ): 'Left',
((loc_B, 'Dirty'), ): 'Suck',
((loc_A, 'Dirty'), (loc_A, 'Clean')): 'Right',
((loc_A, 'Clean'), (loc_B, 'Dirty')): 'Suck',
((loc_B, 'Clean'), (loc_A, 'Dirty')): 'Suck',
((loc_B, 'Dirty'), (loc_B, 'Clean')): 'Left',
((loc_A, 'Dirty'), (loc_A, 'Clean'), (loc_B, 'Dirty')): 'Suck',
((loc_B, 'Dirty'), (loc_B, 'Clean'), (loc_A, 'Dirty')): 'Suck'
}
# create an program and then an object of the TableDrivenAgent
program = TableDrivenAgentProgram(table)
agent = Agent(program)
# create an object of TrivialVacuumEnvironment
environment = TrivialVacuumEnvironment()
# initializing some environment status
environment.status = {loc_A: 'Dirty', loc_B: 'Dirty'}
# add agent to the environment
environment.add_thing(agent)
# run the environment by single step everytime to check how environment evolves using TableDrivenAgentProgram
environment.run(steps=1)
assert environment.status == {(1, 0): 'Clean', (0, 0): 'Dirty'}
environment.run(steps=1)
assert environment.status == {(1, 0): 'Clean', (0, 0): 'Dirty'}
environment.run(steps=1)
assert environment.status == {(1, 0): 'Clean', (0, 0): 'Clean'}
def Model(start, a, b):
print("---Start: {}, (0,0):{} (1,0):{}---".format(start, a, b))
agent = ReflexVacuumAgent()
env = TrivialVacuumEnvironment()
env.add_thing(agent, start)
env.status = {(1, 0): b, (0, 0): a}
while (env.status != {(1, 0): 'Clean', (0, 0): 'Clean'}):
env.step()
return env.agents[0].performance