def __init__(self, SubAgentClass, agent_params={}, state_abstr=None, action_abstr=None, name_ext="-abstr"): ''' Args: SubAgentClass (simple_rl.AgentClass) agent_params (dict): A dictionary with key=param_name, val=param_value, to be given to the constructor for the instance of @SubAgentClass. state_abstr (StateAbstraction) state_abstr (ActionAbstraction) name_ext (str) ''' # Setup the abstracted agent. self.agent = SubAgentClass(**agent_params) self.action_abstr = action_abstr self.state_abstr = state_abstr all_actions = self.action_abstr.get_actions( ) if self.action_abstr is not None else self.agent.actions Agent.__init__(self, name=self.agent.name + name_ext, actions=all_actions)
def __init__(self, SubAgentClass, actions, agent_params={}, state_abstr=None, action_abstr=None, name_ext="abstr"): ''' Args: SubAgentClass (simple_rl.AgentClass) actions (list of str) agent_params (dict): A dictionary with key=param_name, val=param_value, to be given to the constructor for the instance of @SubAgentClass. state_abstr (StateAbstraction) state_abstr (ActionAbstraction) name_ext (str) ''' # Setup the abstracted agent. self.agent = SubAgentClass(actions=actions, **agent_params) self.action_abstr = ActionAbstraction( prim_actions=self.agent.actions ) if action_abstr is None else action_abstr self.state_abstr = StateAbstraction( {}) if state_abstr is None else state_abstr Agent.__init__(self, name=self.agent.name + "-" + name_ext, actions=self.action_abstr.get_actions())
def __init__(self, SubAgentClass, actions, state_abstr=None, action_abstr=None, name_ext="abstr"): ''' Args: SubAgentClass (simple_rl.AgentClass) actions (list of str) state_abstr (StateAbstraction) state_abstr (ActionAbstraction) name_ext (str) ''' # Setup the abstracted agent. self.agent = SubAgentClass(actions=actions) self.action_abstr = ActionAbstraction( options=self.agent.actions, prim_actions=self.agent.actions ) if action_abstr is None else action_abstr self.state_abstr = StateAbstraction( {}) if state_abstr is None else state_abstr Agent.__init__(self, name=self.agent.name + "-" + name_ext, actions=self.action_abstr.get_actions())
def __init__(self, SubAgentClass, actions, mdp_name, max_option_steps=0, state_abstr=None, action_abstr=None, name_ext="abstr"): ''' Args: SubAgentClass (simple_rl.AgentClass) actions (list of str) mdp_name (str) state_abstr (StateAbstraction) state_abstr (ActionAbstraction) name_ext (str) ''' # Setup the abstracted agent. self._create_default_abstractions(actions, state_abstr, action_abstr) self.agent = SubAgentClass(actions=self.action_abstr.get_actions()) self.exp_directory = os.path.join(os.getcwdu(), "results", mdp_name, "options") self.reward_since_tracking = 0 self.max_option_steps = max_option_steps self.num_option_steps = 0 Agent.__init__(self, name=self.agent.name + "-" + name_ext, actions=self.action_abstr.get_actions()) self._setup_files()
def __init__(self, SubAgentClass, sa_stack, aa_stack, cur_level=0, name_ext=""): ''' Args: sa_stack (StateAbstractionStack) aa_stack (ActionAbstractionStack) cur_level (int): Must be in [0:len(state_abstr_stack)] ''' # Setup the abstracted agent. self.state_abstr_stack = sa_stack self.action_abstr_stack = aa_stack self.cur_level = cur_level self.agent = SubAgentClass(actions=self.get_cur_actions()) Agent.__init__(self, name=self.agent.name + "-hierarch" + name_ext, actions=self.get_cur_actions())
def __init__(self, SubAgentClass, agent_params={}, state_abstr=None, action_abstr=None, name_ext="-abstr", n_ops=4, freqs=1000, op_n_episodes=10, op_n_steps=100, max_ops=32, method='eigen', mdp=None): ''' Args: SubAgentClass (simple_rl.AgentClass) agent_params (dict): A dictionary with key=param_name, val=param_value, to be given to the constructor for the instance of @SubAgentClass. state_abstr (StateAbstraction) state_abstr (ActionAbstraction) name_ext (str) ''' # Setup the abstracted agent. self.agent = SubAgentClass(**agent_params) self.action_abstr = action_abstr self.state_abstr = state_abstr all_actions = self.action_abstr.get_actions( ) if self.action_abstr is not None else self.agent.actions self.n_ops = n_ops self.freqs = freqs self.op_n_episodes = op_n_episodes self.op_n_steps = op_n_steps self.max_ops = max_ops self.method = method self.mdp = mdp self.transitions = [] self.n_steps = 0 self.prev_state = None self.cur_n_ops = 0 Agent.__init__(self, name=self.agent.name + name_ext, actions=all_actions)
def __init__(self, SubAgentClass, agent_params={}, feature_mapper=None, name_ext="-feats"): ''' Args: SubAgentClass (simple_rl.AgentClass) agent_params (dict): A dictionary with key=param_name, val=param_value, to be given to the constructor for the instance of @SubAgentClass. feature_mapper (FeatureMapper) name_ext (str) ''' # Setup the abstracted agent. self.agent = SubAgentClass(**agent_params) self.feature_mapper = feature_mapper if self.feature_mapper is not None: name_ext = "-" + feature_mapper.NAME if feature_mapper.NAME is not None else name_ext Agent.__init__(self, name=self.agent.name + name_ext, actions=self.agent.actions)
def __init__(self, SubAgentClass, agent_params={}, state_abstr=None, action_abstr=None, name_ext="-abstr"): ''' Args: SubAgentClass (simple_rl.AgentClass) agent_params (dict): A dictionary with key=param_name, val=param_value, to be given to the constructor for the instance of @SubAgentClass. state_abstr (StateAbstraction) state_abstr (ActionAbstraction) name_ext (str) ''' # Setup the abstracted agent. self.agent = SubAgentClass(**agent_params) self.action_abstr = action_abstr self.state_abstr = state_abstr all_actions = self.action_abstr.get_actions() if self.action_abstr is not None else self.agent.actions Agent.__init__(self, name=self.agent.name + name_ext, actions=all_actions)
def __init__(self, mdp_distr, actions, gamma=0.99, name="$\pi_b^*$"): self.mdp_distr = mdp_distr self.active_mdp_distr = copy.deepcopy(mdp_distr) self.update_policy() Agent.__init__(self, actions=actions, gamma=gamma, name=name)
def reset(self): self.step_number = 0 self.weights = np.zeros(self.num_features * len(self.actions)) Agent.reset(self)
def __init__(self, name, actions, gamma=0.99): Agent.__init__(self, name, actions, gamma) self.reward_history = defaultdict(dict) self.prev_state = None self.prev_action = ""