def create_agent(environment, obs_stacker, agent_type='DQN'):
"""Creates the Hanabi agent.
Args:
environment: The environment.
obs_stacker: Observation stacker object.
agent_type: str, type of agent to construct.
Returns:
An agent for playing Hanabi.
Raises:
ValueError: if an unknown agent type is requested.
"""
if agent_type == 'DQN':
return dqn_agent.DQNAgent(
observation_size=obs_stacker.observation_size(),
num_actions=environment.num_moves(),
num_players=environment.players)
elif agent_type == 'Rainbow':
return rainbow_agent.RainbowAgent(
observation_size=obs_stacker.observation_size(),
num_actions=environment.num_moves(),
num_players=environment.players)
else:
raise ValueError(
'Expected valid agent_type, got {}'.format(agent_type))
def create_adhoc_team(environment, obs_stacker, team_no, rl_shared_model=True):
"""
:param environment:
:param obs_stacker:
:param team:
:return:
"""
agent_repo = ['DQN', 'SimpleAgent', 'Rainbow']
if team_no == 1:
team = {"Rainbow": [0], 'SimpleAgent': [1, 2, 3], }
elif team_no == 2:
team = {'Rainbow': [0, 1], 'SimpleAgent': [2, 3]}
elif team_no == 3:
team = {'Rainbow': [0, 1, 2], 'SimpleAgent': [3]}
else:
print("No valid team number defined!!")
return None
# empty list for agents
# check first if each position is only listed once
set_pos = set()
if not all(agent in agent_repo for agent in team.keys()):
print("Agent doesnt exist!")
return None
# quick check if team is defined correctly
for positions in team.values():
for pos in positions:
# check if team is correctly defined, therefore if
if pos in set_pos or pos not in range(5):
print("TEAM NOT CORRECTLY DEFINED! CHECK positions")
return None
else:
set_pos.add(pos)
list_pos = list(set_pos)
list_pos.sort()
# check if list is sequential
if not all(a == b for a, b in enumerate(list_pos)):
print('Index positions are not sequential')
return None
# create a dictionary for team, which will be returned. for each position
agent_list = [0] * len(list_pos)
for agent_type in team:
agent = None
for pos in team[agent_type]:
if agent_type == 'DQN':
if dqn_agent.DQNAgent.is_rl_agent() and rl_shared_model \
and agent is not None:
agent_list[pos] = agent
else:
agent = dqn_agent.DQNAgent(
observation_size=obs_stacker.observation_size(),
num_actions=environment.num_moves(),
num_players=team_no)
agent_list[pos] = agent
elif agent_type == 'Rainbow':
if dqn_agent.DQNAgent.is_rl_agent() and rl_shared_model \
and agent is not None:
agent_list[pos] = agent
else:
agent = rainbow_agent.RainbowAgent(
observation_size=obs_stacker.observation_size(),
num_actions=environment.num_moves(),
num_players=team_no)
agent_list[pos] = agent
elif agent_type == "SimpleAgent":
if dqn_agent.DQNAgent.is_rl_agent() and rl_shared_model \
and agent is not None:
agent_list[pos] = agent
else:
agent = rule_based_agent.RuleBasedAgent(
players=environment.players)
agent_list[pos] = agent
else:
raise ValueError('Expected valid agent_type, got {}'.format(agent_type))
return agent_list