ray/rllib/tuned_examples/maddpg/two-step-game-maddpg.yaml

35 lines
968 B
YAML

two-step-game-maddpg:
env: ray.rllib.examples.env.two_step_game.TwoStepGame
run: MADDPG
stop:
episode_reward_mean: 7.2
timesteps_total: 20000
config:
# MADDPG only supports tf for now.
framework: tf
env_config:
env_config:
actions_are_logits: true
num_steps_sampled_before_learning_starts: 200
multiagent:
policies:
p0:
- null
- null
- null
- {
agent_id: 0
}
p1:
- null
- null
- null
- {
agent_id: 1
}
# YAML-capable policy_mapping_fn definition via providing a callable class here.
policy_mapping_fn:
type: ray.rllib.examples.multi_agent_and_self_play.policy_mapping_fn.PolicyMappingFn