MPE(multiagent particle environment)是由OpenAI开发的一套时间离散、空间连续的二维多智能体环境,该环境通过控制二维空间中不同角色粒子(particle)的运动来完成一系列任务,使用方法与gym十分类似,目前被广泛用于各类MARL算法的仿真验证。 我的研究方向是多无人机协同控制,相关场景和MPE十分类似,因此我花了两天的时间研究...
Code for a multi-agent particle environment used in the paper "Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments" - multiagent-particle-envs/multiagent/environment.py at master · openai/multiagent-particle-envs
Multi-Agent Particle Environment 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 roo...
def run(agents,sop,environment): while True: # 更新状态,决定下一个行动的agent current_state,current_agent= sop.next(environment,agents) if sop.finished: os.environ.clear() break # agent执行 action = current_agent.step(current_state) # 更新memory memory = process(action) environment.update_me...
MPE（multiagent particle environment）是由OpenAI开发的一套时间离散、空间连续的二维多智能体环境，通过控制二维空间中不同角色粒子（particle）的运动来完成一系列任务，使用方法与gym十分类似，目前被广泛用于各类MARL算法的仿真验证。我的研究方向是多无人机协同控制，相关场景和MPE十分类似，因此我花了...
Code for a multi-agent particle environment used in the paper "Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments" - openai/multiagent-particle-envs