ray/rllib/examples/env/multi_agent.py

import gym

from ray.rllib.env.multi_agent_env import MultiAgentEnv
from ray.rllib.tests.test_rollout_worker import MockEnv, MockEnv2


def make_multiagent(env_name):
    class MultiEnv(MultiAgentEnv):
        def __init__(self, config):
            self.agents = [
                gym.make(env_name) for _ in range(config["num_agents"])
            ]
            self.dones = set()
            self.observation_space = self.agents[0].observation_space
            self.action_space = self.agents[0].action_space

        def reset(self):
            self.dones = set()
            return {i: a.reset() for i, a in enumerate(self.agents)}

        def step(self, action_dict):
            obs, rew, done, info = {}, {}, {}, {}
            for i, action in action_dict.items():
                obs[i], rew[i], done[i], info[i] = self.agents[i].step(action)
                if done[i]:
                    self.dones.add(i)
            done["__all__"] = len(self.dones) == len(self.agents)
            return obs, rew, done, info

    return MultiEnv


class BasicMultiAgent(MultiAgentEnv):
    """Env of N independent agents, each of which exits after 25 steps."""

    def __init__(self, num):
        self.agents = [MockEnv(25) for _ in range(num)]
        self.dones = set()
        self.observation_space = gym.spaces.Discrete(2)
        self.action_space = gym.spaces.Discrete(2)
        self.resetted = False

    def reset(self):
        self.resetted = True
        self.dones = set()
        return {i: a.reset() for i, a in enumerate(self.agents)}

    def step(self, action_dict):
        obs, rew, done, info = {}, {}, {}, {}
        for i, action in action_dict.items():
            obs[i], rew[i], done[i], info[i] = self.agents[i].step(action)
            if done[i]:
                self.dones.add(i)
        done["__all__"] = len(self.dones) == len(self.agents)
        return obs, rew, done, info


class EarlyDoneMultiAgent(MultiAgentEnv):
    """Env for testing when the env terminates (after agent 0 does)."""

    def __init__(self):
        self.agents = [MockEnv(3), MockEnv(5)]
        self.dones = set()
        self.last_obs = {}
        self.last_rew = {}
        self.last_done = {}
        self.last_info = {}
        self.i = 0
        self.observation_space = gym.spaces.Discrete(10)
        self.action_space = gym.spaces.Discrete(2)

    def reset(self):
        self.dones = set()
        self.last_obs = {}
        self.last_rew = {}
        self.last_done = {}
        self.last_info = {}
        self.i = 0
        for i, a in enumerate(self.agents):
            self.last_obs[i] = a.reset()
            self.last_rew[i] = None
            self.last_done[i] = False
            self.last_info[i] = {}
        obs_dict = {self.i: self.last_obs[self.i]}
        self.i = (self.i + 1) % len(self.agents)
        return obs_dict

    def step(self, action_dict):
        assert len(self.dones) != len(self.agents)
        for i, action in action_dict.items():
            (self.last_obs[i], self.last_rew[i], self.last_done[i],
             self.last_info[i]) = self.agents[i].step(action)
        obs = {self.i: self.last_obs[self.i]}
        rew = {self.i: self.last_rew[self.i]}
        done = {self.i: self.last_done[self.i]}
        info = {self.i: self.last_info[self.i]}
        if done[self.i]:
            rew[self.i] = 0
            self.dones.add(self.i)
        self.i = (self.i + 1) % len(self.agents)
        done["__all__"] = len(self.dones) == len(self.agents) - 1
        return obs, rew, done, info


class RoundRobinMultiAgent(MultiAgentEnv):
    """Env of N independent agents, each of which exits after 5 steps.

    On each step() of the env, only one agent takes an action."""

    def __init__(self, num, increment_obs=False):
        if increment_obs:
            # Observations are 0, 1, 2, 3... etc. as time advances
            self.agents = [MockEnv2(5) for _ in range(num)]
        else:
            # Observations are all zeros
            self.agents = [MockEnv(5) for _ in range(num)]
        self.dones = set()
        self.last_obs = {}
        self.last_rew = {}
        self.last_done = {}
        self.last_info = {}
        self.i = 0
        self.num = num
        self.observation_space = gym.spaces.Discrete(10)
        self.action_space = gym.spaces.Discrete(2)

    def reset(self):
        self.dones = set()
        self.last_obs = {}
        self.last_rew = {}
        self.last_done = {}
        self.last_info = {}
        self.i = 0
        for i, a in enumerate(self.agents):
            self.last_obs[i] = a.reset()
            self.last_rew[i] = None
            self.last_done[i] = False
            self.last_info[i] = {}
        obs_dict = {self.i: self.last_obs[self.i]}
        self.i = (self.i + 1) % self.num
        return obs_dict

    def step(self, action_dict):
        assert len(self.dones) != len(self.agents)
        for i, action in action_dict.items():
            (self.last_obs[i], self.last_rew[i], self.last_done[i],
             self.last_info[i]) = self.agents[i].step(action)
        obs = {self.i: self.last_obs[self.i]}
        rew = {self.i: self.last_rew[self.i]}
        done = {self.i: self.last_done[self.i]}
        info = {self.i: self.last_info[self.i]}
        if done[self.i]:
            rew[self.i] = 0
            self.dones.add(self.i)
        self.i = (self.i + 1) % self.num
        done["__all__"] = len(self.dones) == len(self.agents)
        return obs, rew, done, info


MultiAgentCartPole = make_multiagent("CartPole-v0")
MultiAgentMountainCar = make_multiagent("MountainCarContinuous-v0")
MultiAgentPendulum = make_multiagent("Pendulum-v0")