agent_params['gamma'] = params['gamma']
agent_params['predict_mode'] = params['predict_mode']
agent_params['trained_model_path'] = params['trained_model_path']
agent_params['warm_start'] = params['warm_start']
agent_params['cmd_input_mode'] = params['cmd_input_mode']
if agt == 0:
agent = AgentCmd(movie_kb, act_set, slot_set, agent_params)
elif agt == 1:
agent = InformAgent(movie_kb, act_set, slot_set, agent_params)
elif agt == 2:
agent = RequestAllAgent(movie_kb, act_set, slot_set, agent_params)
elif agt == 3:
agent = RandomAgent(movie_kb, act_set, slot_set, agent_params)
elif agt == 4:
agent = EchoAgent(movie_kb, act_set, slot_set, agent_params)
elif agt == 5:
agent = RequestBasicsAgent(movie_kb, act_set, slot_set, agent_params)
elif agt == 9:
agent = AgentDQN(movie_kb, act_set, slot_set, agent_params)
################################################################################
# Add your agent here
################################################################################
else:
pass
################################################################################
# Parameters for User Simulators
################################################################################
usersim_params = {}
agent_params['predict_mode'] = params['predict_mode']
agent_params['trained_model_path'] = params['trained_model_path']
agent_params['warm_start'] = params['warm_start']
agent_params['cmd_input_mode'] = params['cmd_input_mode']
if agt == 0:
agent = AgentCmd(course_kb, act_set, slot_set, agent_params)
elif agt == 1:
agent = InformAgent(course_kb, act_set, slot_set, agent_params)
elif agt == 2:
agent = RequestAllAgent(course_kb, act_set, slot_set, agent_params)
elif agt == 3:
agent = RandomAgent(course_kb, act_set, slot_set, agent_params)
elif agt == 4:
agent = EchoAgent(course_kb, act_set, slot_set, agent_params)
elif agt == 5:
agent = RequestBasicsAgent(course_kb, act_set, slot_set, agent_params)
elif agt == 9:
agent = AgentDQN(course_kb, act_set, slot_set, agent_params)
################################################################################
# Add your agent here
################################################################################
else:
pass
################################################################################
# Parameters for User Simulators
################################################################################
usersim_params = {}
agent_params['gamma'] = params['gamma']
agent_params['predict_mode'] = params['predict_mode']
agent_params['trained_model_path'] = params['trained_model_path']
agent_params['warm_start'] = params['warm_start']
agent_params['cmd_input_mode'] = params['cmd_input_mode']
if agt == 0:
agent = AgentCmd(kb, act_set, slot_set, agent_params)
elif agt == 1:
agent = InformAgent(kb, act_set, slot_set, agent_params)
elif agt == 2:
agent = RequestAllAgent(kb, act_set, slot_set, agent_params)
elif agt == 3:
agent = RandomAgent(kb, act_set, slot_set, agent_params)
elif agt == 4:
agent = EchoAgent(kb, act_set, slot_set, agent_params)
elif agt == 5: # movie request rule agent
agent = RequestBasicsAgent(kb, act_set, slot_set, agent_params,
movie_request_slots)
elif agt == 6: # restaurant request rule agent
agent = RequestBasicsAgent(kb, act_set, slot_set, agent_params,
restaurant_request_slots)
elif agt == 7: # taxi request agent
agent = RequestBasicsAgent(kb, act_set, slot_set, agent_params,
taxi_request_slots)
elif agt == 8: # taxi request-inform rule agent
agent = RequestInformSlotAgent(kb, act_set, slot_set, agent_params,
taxi_request_slots, taxi_inform_slots)
elif agt == 9: # DQN agent for movie domain
agent = AgentDQN(kb, act_set, slot_set, agent_params)
agent.initialize_config(dialog_config.movie_request_slots,