2、cdmultiagent-particle-envs 3、pip install -e . 即可。 二、simple_world_comm环境详解 multiagent-particle-envs基于gym开发,所以环境创建流程基本于gym一致。multiagent-particle-envs包含9个环境,分别为simple、simple_adversary、simple_crypto、simple_push、simple_reference、simple_speaker_listener、simple_...
GitHub - openai/multiagent-particle-envs: Code for a multi-agent particle environment used in the paper "Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments"github.com/openai/multiagent-particle-envs p.s. MPE中粒子的运动既可以是离散的(前后左右四个方向),也可以是连续的(x...
A simple multi-agent particle world with a continuous observation and discrete action space, along with some basic simulated physics. Used in the paper Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments.Getting started:To install, cd into the root directory and type pip install ...
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Code for a multi-agent particle environment used in the paper "Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments" - multiagent-particle-envs/multiagent/rendering.py at master · openai/multiagent-particle-envs
class MultiAgentEnv(gym.Env): metadata = { 'render.modes' : ['human', 'rgb_array'] } def __init__(self, world, reset_callback=None, reward_callback=None, observation_callback=None, info_callback=None, done_callback=None, shared_viewer=True): self.world = world self.agents = ...
make_env.py: contains code for importing a multiagent environment as an OpenAI Gym-like object. ./multiagent/environment.py: contains code for environment simulation (interaction physics, _step() function, etc.) ./multiagent/core.py: contains classes for various objects (Entities, Landmarks, ...
particle 由COLUMBIA UNIVERSITY的CREATIVE MACHINES LAB研发,看上去很优美,单体执行器在身体上方,依靠集群才能进行移动。 0 tribots 由洛桑理工的Reconfigurable Robotics Lab开发,该实验室开发了许多由三个相同单元构成机器人,同时崔这些机器人的合作进行了许多研究。 0 Bill-E 由MIT's Center for Bits and Atoms开...
然后再次定义env.reset()，env.step()，env.render()等方法，这些方法中的具体操作都是直接调用env.env已有的方法，另外，还需要定义env.get_obs()，env.get_state()等方法配合Pymarl的算法。对应的框架图如下，具体可参考FACMAC代码。局限 我在准备编写环境的时候发现MPE有个很大的局限性——单个智能...
The problem of prng is that the gym package is updating, and prng function has been deleted. you can fix this in code multiagent-particle-envs/multiagent/multi_discrete.py import gym # from gym.spaces import prng # this prng has been can...