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Aug, 2021
连续动作空间下的多智能体系统安全强化学习
Safe Deep Reinforcement Learning for Multi-Agent Systems with Continuous Action Spaces
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Ziyad Sheebaelhamd, Konstantinos Zisis, Athina Nisioti, Dimitris Gkouletsos, Dario Pavllo...
TL;DR
本文介绍了在深度强化学习模型中添加安全层以确保多智能体控制问题的安全性的方法,该方法采用线性化单步转换动态的思想,并使用软约束解决了实施步骤中的不可行性问题,在保证软约束的约束满足性的基础上实现了学习过程中的安全控制。
Abstract
multi-agent control
problems constitute an interesting area of application for
deep reinforcement learning
models with continuous action spaces. Such real-world applications, however, typically come with critical
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