Mean-Payoff Games with ω-Regular Specifications

Author:

Gutierrez JulianORCID,Steeples ThomasORCID,Wooldridge MichaelORCID

Abstract

Multi-player mean-payoff games are a natural formalism for modelling the behaviour of concurrent and multi-agent systems with self-interested players. Players in such a game traverse a graph, while attempting to maximise a (mean-)payoff function that depends on the play generated. As with all games, the equilibria that could arise may have undesirable properties. However, as system designers, we typically wish to ensure that equilibria in such systems correspond to desirable system behaviours, for example, satisfying certain safety or liveness properties. One natural way to do this would be to specify such desirable properties using temporal logic. Unfortunately, the use of temporal logic specifications causes game theoretic verification problems to have very high computational complexity. To address this issue, we consider ω-regular specifications. These offer a concise and intuitive way of specifying system behaviours with a comparatively low computational overhead. The main results of this work are characterisation and complexity bounds for the problem of determining if there are equilibria that satisfy a given ω-regular specification in a multi-player mean-payoff game in a number of computationally relevant game-theoretic settings.

Publisher

MDPI AG

Subject

Applied Mathematics,Statistics, Probability and Uncertainty,Statistics and Probability

Reference44 articles.

1. Alternating-time temporal logic

2. Concurrent omega-regular games

3. Positional strategies for mean payoff games

4. The Complexity of Nash Equilibria in Limit-Average Games;Ummels;arXiv,2011

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3