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Safe Multi|Agent Reinforcement Learning for Multi|Robot Control


Safe multi-agent reinforcement learning for multi-robot control

Yet, developing multi-robot control methods from the perspective of safe multi-agent reinforcement learning (MARL) has merely been studied. To fill this gap, in ...

Safe multi-agent reinforcement learning for multi-robot control

In this study, we investigate safe MARL for multi-robot control on cooperative tasks, in which each individual robot has to not only meet its own safety ...

Safe Multi-Agent Reinforcement Learning for Formation Control ...

In this paper, we address the problem of behavior-based formation control of mobile robots, where we use safe multi-agent reinforcement learning ...

Safe Multi-Agent Reinforcement Learning for Multi-Robot Control

Safe Multi-Agent Reinforcement Learning for Multi-Robot Control. Shangding Gua∗, Jakub Grudzien Kubab∗, Yuanpei Chenc, Yali Dud, Long.

aij-safe-marl - Google Sites

To our knowledge, no study has considered multi-robot control from the perspective of safe Multi-Agent reinforcement learning (MARL). To fill this gap, in this ...

Safe Multi-Agent Reinforcement Learning for Formation Control ...

In this paper, we address the problem of behavior-based formation control of mobile robots, where we use safe multi-agent reinforcement learning (MARL) to ...

Safe Multi-Agent Reinforcement Learning for Multi-Robot Control

In [28] , the multiagent TRPO was developed to achieve theoretical assurances of both monotonically improving rewards and fulfilling safety constraints. Despite ...

chauncygu/Safe-Multi-Agent-Mujoco - GitHub

In particular, the background environment, agents, physics simulator, and the reward function are preserved. However, as oppose to its predecessor, Safe ...

Safe multi-agent reinforcement learning for multi-robot control

Abstract. A challenging problem in robotics is how to control multiple robots cooperatively and safely in real-world applications. Yet, ...

Safe multi-agent motion planning via filtered reinforcement learning

Abstract: We study the problem of safe multi-agent motion planning in cluttered environments. Existing multi-agent reinforcement learning-based motion ...

Safe Multi-Agent Reinforcement Learning through Decentralized ...

Abstract. Multi-Agent Reinforcement Learning (MARL) algorithms show amazing performance in simulation in recent years, but placing MARL in real-world ...

Near-Optimal Multi-Agent Learning for Safe Coverage Control

[12] Matteo Turchetta, Felix Berkenkamp, and Andreas Krause. Safe exploration for interactive machine learning. Advances in Neural Information Processing ...

Learning safe control for multi-robot systems - Kunal Garg

In more recent multi-agent reinforcement learning (MARL) work (Zhang et al., 2018), the authors allow the agents to communicate over a time- ...

Multi-Agent Deep Reinforcement Learning for Multi-Robot Applications

In this paper, we are especially interested in multi-agent deep reinforcement learning, where multiple agents present in the environment not only learn from ...

CAMA: A New Framework for Safe Multi-Agent Reinforcement ...

Abstract: With the widespread application of multi-agent reinforcement learning (MARL) in real-life settings, the ability to meet safety ...

Safe multi-agent reinforcement learning for multi-robot control - OUCI

Safe multi-agent reinforcement learning for multi-robot control · Shangding Gu · Jakub Grudzien Kuba · Yuanpei Chen · Yali Du · Long Yang · Alois Knoll · Yaodong Yang ...

Reinforcement Learning in Robotics : r/robotics - Reddit

Over simulations, the RL agent will learn what actions will make it reach the goal. If you look atthis paper orthis paper you will see that ...

Safe multi-agent reinforcement learning for multi-robot control.

Safe multi-agent reinforcement learning for multi-robot control · Abstract · Categories · Keywords · Reprint years · DOI · Other Versions.

Safe Multi-Agent Reinforcement Learning through Decentralized ...

Safe Multi-Agent Reinforcement Learning through Decentralized Multiple Control Barrier Functions · Zhiyuan Cai, Huanhui Cao, +2 authors. Hao Xiong · Published in ...

Distributed safe reinforcement learning for multi-robot motion planning

In [15], a value iteration Heuristic DP algorithm is proposed to solve the dynamic graphical games of discrete-time multi-agent systems. For continuous-time.