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arXiv 2210.01732eess.SYcs.SY
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基于CaTL+规范的多智能体鲁棒协调

Robust Multi-Agent Coordination from CaTL+ Specifications

Wenliang Liu, Kevin Leahy, Zachary Serlin, Calin Belta

AI总结:

本文将CaTL扩展为更具表达力的CaTL+逻辑,提出传统鲁棒性和指数鲁棒性两种度量,并通过两步优化方法实现多智能体控制综合,仿真验证了方法的有效性。

摘要:

我们考虑控制一个需要满足时序逻辑要求的异构多智能体系统的问题。能力时序逻辑(CaTL)最近被提出,用于形式化部署具有不同能力和合作要求的自主智能体团队的此类规范。在本文中,我们将CaTL扩展为一种新的逻辑CaTL+,它比CaTL更具表达力,并且具有在所有智能体共享的连续工作空间上的语义。我们为CaTL+定义了两个新的鲁棒性度量:传统鲁棒性和指数鲁棒性。后者是可靠的,几乎处处可微,并且消除了掩蔽现象,这是传统鲁棒性度量的主要局限之一。我们形式化了一个控制综合问题以最大化CaTL+鲁棒性,并提出了一种两步优化方法来解决该问题。仿真结果展示了CaTL+增强的表达能力以及所提出的控制综合方法的有效性。

英文摘要:

We consider the problem of controlling a heterogeneous multi-agent system required to satisfy temporal logic requirements. Capability Temporal Logic (CaTL) was recently proposed to formalize such specifications for deploying a team of autonomous agents with different capabilities and cooperation requirements. In this paper, we extend CaTL to a new logic CaTL+, which is more expressive than CaTL and has semantics over a continuous workspace shared by all agents. We define two novel robustness metrics for CaTL+: the traditional robustness and the exponential robustness. The latter is sound, differentiable almost everywhere and eliminates masking, which is one of the main limitations of the traditional robustness metric. We formulate a control synthesis problem to maximize CaTL+ robustness and propose a two-step optimization method to solve this problem. Simulation results are included to illustrate the increased expressivity of CaTL+ and the efficacy of the proposed control synthesis approach.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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