MPE代码分析 MPE中包含三个最为重要的对象,scenario,world和env,其中scenario是一个静态的场景对象,用于构造环境模拟器以及计算不同状态下环境模拟器内的参数,world是动态的环境模拟器对象,env则通过接收算法提供的智能体控制环境模拟器,三者之间的关系大致可以用这张图表示,接下来我将一一介绍这三个对象。 scenario对象...
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...
Star561 master BranchesTags Code Folders and files Name Last commit message Last commit date Latest commit History 12 Commits common maddpg model/simple_tag README.md agent.py main.py runner.py MADDPG This is a pytorch implementation of MADDPG onMulti-Agent Particle Environment(MPE), the correspo...
The Multi-Agent Particle Environments (MPE) were introduced as part of Mordatch and Abbeel [2017] and first released as part of Lowe et al. [2017]. These are 9 communication oriented environments where particle agents can (sometimes) move, communicate, see each other, push each other around...
The proposed method is tested in the multi-agent particle environment (MPE). Experimental results show that our method, apart from correcting for the bias estimation, outperforms MATD3 and MADDPG methods in terms of overall returns. We also perform experiments to test the effect of a weighted ...
We evaluate our methods by four challenging tasks, three of which are based on the multi-agent particle environment (MPE) [29], and the other is a fully cooperative football game [30]. Experiments show that our algorithm can form an effective interactive network, leading to a higher reward ...
Evaluation of CoHet in the Multi-agent Particle Environment (MPE) and Vectorized Multi-Agent Simulator (VMAS) benchmarks demonstrates superior performance compared to the state-of-the-art in a range of cooperative multi-agent scenarios. Our research is supplemented by an analysis of the impact ...
Also includes multiple environments, including the proposed suite of partially-observable environments, MPE (https://github.com/openai/multiagent-particle-envs), KiloBots simulator, and RCSServer3D for the FCPortugal3d team. Get data from GitHub Open Data for download under the CC BY licence ...
Please see the football repository to install the football environment. 3.Train Here we use train_mpe.sh as an example: cd onpolicy/scripts chmod +x ./train_mpe.sh ./train_mpe.sh Local results are stored in subfold scripts/results. Note that we use Weights & Bias as the default visu...
MPE: A set of simple nongraphical communication tasks, originally from https://github.com/openai/multiagent-particle-envs SISL: 3 cooperative environments, originally from https://github.com/sisl/MADRL Installation To install the base PettingZoo library: pip install pettingzoo. This does not includ...