def run_dqn_algorithm(parameter_files):
exp_dir = "tmp_exp_dir"
diadem_params = Params(filename=parameter_files)
environment = DiademBarkEnvironment(runtime=runtime)
context = AgentContext(environment=environment,
datamanager=None,
preprocessor=None,
optimizer=tf.train.AdamOptimizer,
summary_service=ConsoleSummary())
agent = AgentManager(params=diadem_params, context=context)
exp = Experiment(params=diadem_params['experiment'],
main_dir=exp_dir,
context=context,
agent=agent,
visualizer=None)
exp.run()
def run_dqn_algorithm(parameter_files):
exp_dir = "tmp_exp_dir"
params = Params(filename=parameter_files)
environment = BarkHighway(params=params['environment'])
context = AgentContext(environment=environment,
datamanager=None,
preprocessor=Normalization(environment=environment),
optimizer=tf.train.AdamOptimizer,
summary_service=PandasSummary())
agent = AgentManager(params=params, context=context)
exp = Experiment(params=params['experiment'],
main_dir=exp_dir,
context=context,
agent=agent,
visualizer=None)
exp.run()
def main():
exp_dir = "tmp_exp_dir"
params = Params(filename=[
"examples/example_params/common_parameters.yaml",
"examples/example_params/online_rendering.yaml"
])
environment = GymEnvironment(params=params['environment'])
context = AgentContext(environment=environment,
datamanager=None,
preprocessor=Normalization(environment=environment),
optimizer=tf.train.AdamOptimizer,
summary_service=ConsoleSummary())
agent = AgentManager(params=params, context=context)
exp = Experiment(params=params['experiment'],
main_dir=exp_dir,
context=context,
agent=agent,
visualizer=OnlineVisualizer(
params=params['visualization'], context=context))
exp.run()