This is an unified framework which can used by researchers to study multi-robot reinforcement learning in multi-robot systems. MultiRoboLearn builds an open-source framework for multi-robot systems.

Existing multi-agent coordination techniques are often fragile and vulnerable to anomalies such as agent attrition and communication disturbances, which are quite common in the real-world deployment ...

In this paper, we apply deep reinforcement learning (DRL) to solve the flocking control problem of multi-robot systems in complex environments with dynamic obstacles. Starting from the traditional ...

The Multi-agent reinforcement learning algorithms can also identify when an agent or robot is doing something that doesn't contribute to the goal. Researchers tested their algorithms using simulated ...

The code is based on gym and makes use of some of the scenarios from VMAS: Vectorized Multi-Agent Simulator. sampling scenario is reimplemented to fit the version used in the paper. Besides, the ...

Keywords: multi-agent reinforcement learning, game theory, deep learning, artificial intelligence, actor–critic algorithm, multi-agent, Stackelberg, decentralized learning schemes, reinforcement ...