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_spread、simple_tag、simple_world_comm。其中simple环境仅作验证环境是否安装成功的测试使用,其余环...
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...
首先,从github上下载完整的zip压缩包(multiagent-particle-envs-master.zip)到本地。解压后,复制路径名(包括multiagent-particle-envs-master文件夹)备用,打开cmd/Anaconda Prompt,**你要安装到的环境,输入以下命令pip install -e (path name) 安装成功后,可以用以下代码检验。
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
Particle Swarm OptimizationPower SystemValve Point EffectA new versatile optimization, the particle swarm optimization based on multi-agent system (MAPSO) is presented. The economic load dispatch (ELD) problem of power system can be solved by the algorithm. By competing and cooperating with the ...
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...
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...
multiagentparticleenvs是一个用于模拟和训练多智能体强化学习算法的开源环境。在这个环境中,用户可以创建和管理多个智能体,这些智能体可以在不同的环境中进行交互和决策。 这个环境提供了丰富的功能和工具,包括粒子系统、强化学习算法库、可视化工具等。用户可以自定义粒子系统,设置粒子的速度、方向和位置等属性,以及控制...
multi-agent particle environment三种任务: Cooperative Navigation Cooperative Navigation:N个agent合作到达L个地标,同时避免碰撞 DDPG的策略更具侵略性,即多个agent通常同时接近一个里程碑,这可能会导致碰撞。 CommNet和BiCNet代理都比较保守,也就是说,他们更愿意避免碰撞,而不是夺取一个地标,这最终会导致一小部分被占...
To overcome particle impoverishment, a simultaneous localization and mapping (SLAM) method based on multi-agent particle swarm optimized particle filter (MAPSOPF) was presented by introducing the idea of multi-agent to the particle swarm optimized particle filter (PSOPF) which is an algorithm for SL...