def get_policy_graph_values(self) -> common.Graph2DValues:
policy: TabularPolicy = self.algorithm.target_policy
x_list: list[int] = []
y_list: list[float] = []
for s, state in enumerate(self.environment.states):
if not state.is_terminal:
x_list.append(state.capital)
action: Action = policy.get_action(s) # type: ignore
y_list.append(float(action.stake))
# print(state.capital, v[state])
x_values = np.array(x_list, dtype=int)
y_values = np.array(y_list, dtype=float)
g: common.Graph2DValues = common.Graph2DValues()
g.x_series = common.Series(title=g.x_label, values=x_values)
g.graph_series = [common.Series(title=g.y_label, values=y_values)]
g.title = "Policy"
g.x_label = "Capital"
g.y_label = "Stake"
g.x_min = 0.0
g.x_max = 100.0
g.y_min = 0.0
g.y_max = None
g.has_grid = True
g.has_legend = False
return g
def create(self) -> Comparison:
return Comparison(
environment_parameters=EnvironmentParameters(),
comparison_settings=Settings(),
breakdown_parameters=common.BreakdownParameters(
breakdown_type=common.BreakdownType.RETURN_BY_EPISODE),
settings_list=[
# Settings(algorithm_parameters=common.AlgorithmParameters(
# algorithm_type=common.AlgorithmType.EXPECTED_SARSA,
# alpha=0.9
# )),
# Settings(algorithm_parameters=common.AlgorithmParameters(
# algorithm_type=common.AlgorithmType.VQ,
# alpha=0.2
# )),
Settings(algorithm_parameters=common.AlgorithmParameters(
algorithm_type=common.AlgorithmType.TABULAR_Q_LEARNING,
alpha=0.5)),
Settings(algorithm_parameters=common.AlgorithmParameters(
algorithm_type=common.AlgorithmType.TABULAR_SARSA,
alpha=0.5)),
],
# settings_list_multiprocessing=common.ParallelContextType.SPAWN,
graph2d_values=common.Graph2DValues(
has_grid=True,
has_legend=True,
moving_average_window_size=19,
y_min=-100,
y_max=0,
),
grid_view_parameters=common.GridViewParameters(show_demo=True,
show_q=True))
def create(self) -> Comparison:
return Comparison(
environment_parameters=EnvironmentParameters(),
comparison_settings=common.Settings(
runs=10,
# runs_multiprocessing=common.ParallelContextType.FORK_GLOBAL,
training_episodes=100,
# display_every_step=True,
),
breakdown_parameters=common.BreakdownAlgorithmByAlpha(
breakdown_type=common.BreakdownType.RETURN_BY_ALPHA,
alpha_min=0.1,
alpha_max=1.0,
alpha_step=0.1,
algorithm_type_list=[
common.AlgorithmType.TABULAR_EXPECTED_SARSA,
common.AlgorithmType.TABULAR_VQ,
common.AlgorithmType.TABULAR_Q_LEARNING,
common.AlgorithmType.TABULAR_SARSA
],
),
settings_list_multiprocessing=common.ParallelContextType.
FORK_GLOBAL,
graph2d_values=common.Graph2DValues(
has_grid=True,
has_legend=True,
y_min=-140,
y_max=0,
),
grid_view_parameters=common.GridViewParameters(show_policy=True,
show_q=True))
def create(self) -> Comparison:
# TODO: Make work, once multiprocessing
return Comparison(
environment_parameters=EnvironmentParameters(),
comparison_settings=common.Settings(
runs=1,
training_episodes=100_000,
),
breakdown_parameters=common.BreakdownAlgorithmByAlpha(
breakdown_type=common.BreakdownType.RETURN_BY_ALPHA,
alpha_min=0.1,
alpha_max=1.0,
alpha_step=0.05,
algorithm_type_list=[
common.AlgorithmType.TABULAR_EXPECTED_SARSA,
# common.AlgorithmType.VQ,
common.AlgorithmType.TABULAR_Q_LEARNING,
common.AlgorithmType.TABULAR_SARSA
],
),
settings_list_multiprocessing=common.ParallelContextType.SPAWN,
graph2d_values=common.Graph2DValues(
has_grid=True,
has_legend=True,
y_min=-140,
y_max=0,
),
)
def create(self):
return Comparison(
# environment_parameters=EnvironmentParameters(),
comparison_settings=Settings(),
settings_list=[
Settings(
algorithm_parameters=common.AlgorithmParameters(
theta=0.00001, # accuracy of policy_evaluation
algorithm_type=common.AlgorithmType.
DP_VALUE_ITERATION_V,
verbose=True), ),
],
graph2d_values=common.Graph2DValues(),
)
def create(self):
return Comparison(
environment_parameters=EnvironmentParameters(),
comparison_settings=Settings(),
breakdown_parameters=common.BreakdownParameters(
breakdown_type=common.BreakdownType.RMS_BY_EPISODE, ),
settings_list=[
Settings(algorithm_parameters=AlgorithmParameters(
algorithm_type=common.AlgorithmType.TABULAR_TD_0,
alpha=0.05,
)),
Settings(algorithm_parameters=AlgorithmParameters(
algorithm_type=common.AlgorithmType.TABULAR_TD_0,
alpha=0.1,
)),
Settings(algorithm_parameters=AlgorithmParameters(
algorithm_type=common.AlgorithmType.TABULAR_TD_0,
alpha=0.15,
)),
Settings(algorithm_parameters=AlgorithmParameters(
algorithm_type=common.AlgorithmType.MC_CONSTANT_ALPHA,
alpha=0.01,
)),
Settings(algorithm_parameters=AlgorithmParameters(
algorithm_type=common.AlgorithmType.MC_CONSTANT_ALPHA,
alpha=0.02,
)),
Settings(algorithm_parameters=AlgorithmParameters(
algorithm_type=common.AlgorithmType.MC_CONSTANT_ALPHA,
alpha=0.03,
)),
Settings(algorithm_parameters=AlgorithmParameters(
algorithm_type=common.AlgorithmType.MC_CONSTANT_ALPHA,
alpha=0.04,
)),
],
settings_list_multiprocessing=common.ParallelContextType.
FORK_GLOBAL,
graph2d_values=common.Graph2DValues(has_grid=True,
has_legend=True,
y_min=0.0,
y_max=0.25),
grid_view_parameters=common.GridViewParameters(
show_result=True,
show_v=True,
),
)
def create(self):
# TODO: Problem with the first step not learning and crashing?
# Try grids.TRACK_1 for example (3rd position crash)
return Comparison(
environment_parameters=EnvironmentParameters(
grid=grids.TRACK_3,
extra_reward_for_failure=-100.0, # 0.0 in problem statement
skid_probability=0.1,
),
comparison_settings=Settings(),
breakdown_parameters=common.BreakdownParameters(
breakdown_type=common.BreakdownType.RETURN_BY_EPISODE
),
settings_list=[
# Settings(algorithm_parameters=common.AlgorithmParameters(
# algorithm_type=common.AlgorithmType.EXPECTED_SARSA,
# alpha=0.9
# )),
# Settings(algorithm_parameters=common.AlgorithmParameters(
# algorithm_type=common.AlgorithmType.VQ,
# alpha=0.2
# )),
# Settings(algorithm_parameters=common.AlgorithmParameters(
# algorithm_type=common.AlgorithmType.Q_LEARNING,
# alpha=0.5
# )),
Settings(algorithm_parameters=common.AlgorithmParameters(
algorithm_type=common.AlgorithmType.MC_CONTROL_OFF_POLICY,
initial_q_value=-40.0,
)),
],
# settings_list_multiprocessing=common.ParallelContextType.SPAWN,
graph2d_values=common.Graph2DValues(
has_grid=True,
has_legend=True,
moving_average_window_size=101,
y_min=-200,
y_max=0
),
grid_view_parameters=common.GridViewParameters(
grid_view_type=common.GridViewType.POSITION,
show_demo=True,
show_trail=True
)
)
def create(self) -> Comparison:
return Comparison(
environment_parameters=EnvironmentParameters(
random_wind=self._random_wind, ),
comparison_settings=Settings(),
breakdown_parameters=common.BreakdownParameters(
breakdown_type=common.BreakdownType.EPISODE_BY_TIMESTEP, ),
settings_list=[
Settings(algorithm_parameters=common.AlgorithmParameters(
algorithm_type=common.AlgorithmType.TABULAR_SARSA,
alpha=0.5,
initial_q_value=0.0,
))
],
graph2d_values=common.Graph2DValues(
has_grid=True,
has_legend=True,
),
grid_view_parameters=common.GridViewParameters(
show_demo=True,
show_q=True,
))
def get_state_graph_values(self) -> common.Graph2DValues:
x_list: list[int] = []
y_list: list[float] = []
for s, state in enumerate(self.environment.states):
if not state.is_terminal:
x_list.append(state.capital)
y_list.append(self.algorithm.V[s])
# print(state.capital, v[state])
x_values = np.array(x_list, dtype=int)
y_values = np.array(y_list, dtype=float)
g: common.Graph2DValues = common.Graph2DValues()
g.x_series = common.Series(title=g.x_label, values=x_values)
g.graph_series = [common.Series(title=g.y_label, values=y_values)]
g.title = "V(s)"
g.x_label = "Capital"
g.y_label = "V(s)"
g.x_min = 0.0
g.x_max = 100.0
g.y_min = 0.0
g.y_max = 1.0
g.has_grid = True
g.has_legend = False
return g
