在享乐游戏中放松核心稳定性

IF 4.6 2区 计算机科学 Q1 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Angelo Fanelli , Gianpiero Monaco , Luca Moscardelli
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引用次数: 0

摘要

核心是游戏中一个众所周知的基本稳定性概念,用于模拟联盟的形成,如享乐游戏:如果不存在阻塞联盟,即没有一组代理可以通过组成联盟来获利,则结果是核心稳定的。事实上,阻塞联盟的基数,即必须协调自己的偏离代理的数量,可以任意高,并且代理可能只从他们的偏离中获得很小的收益,而他们可能会因偏离而产生更高的成本,这表明核心无法适当地模拟大型和高度分布式的多代理系统中的实际场景。出于这个原因,我们考虑宽松的核心稳定结果,其中允许偏差的概念沿着两个正交方向进行修改:前者考虑了偏离联盟的大小q,后者考虑了偏离联盟中每个成员的乘法因子k的效用增益量。这些变化导致了两种不同的稳定性概念,即q-size核心和k-improvement核心。我们考虑分数型享乐对策,这是一个众所周知的享乐对策的子类,它的核心稳定结果不能保证存在,并且计算上难以确定核心的非空性;我们通过在许多情况下提供紧或几乎紧的边界,从无政府状态的价格和稳定的价格的角度,研究了这些宽松的稳定性概念的存在性、可计算性和性能。有趣的是,所考虑的核的松弛概念也具有吸引人的性质,在一些值得注意的情况下,恢复了收敛性、存在性和在多项式时间内计算稳定解的可能性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Relaxed core stability in hedonic games
The core is a well-known and fundamental notion of stability in games intended to model coalition formation such as hedonic games: an outcome is core stable if there exists no blocking coalition, i.e., no set of agents that may profit by forming a coalition together. The fact that the cardinality of a blocking coalition, i.e., the number of deviating agents that have to coordinate themselves, can be arbitrarily high, and the fact that agents may benefit only by a tiny amount from their deviation, while they could incur in a higher cost for deviating, suggest that the core is not able to suitably model practical scenarios in large and highly distributed multi-agent systems. For this reason, we consider relaxed core stable outcomes where the notion of permissible deviations is modified along two orthogonal directions: the former takes into account the size q of the deviating coalition, and the latter the amount of utility gain, in terms of a multiplicative factor k, for each member of the deviating coalition. These changes result in two different notions of stability, namely, the q-size core and k-improvement core. We consider fractional hedonic games, that is a well-known subclass of hedonic games for which core stable outcomes are not guaranteed to exist and it is computationally hard to decide non-emptiness of the core; we investigate these relaxed concepts of stability with respect to their existence, computability and performance in terms of price of anarchy and price of stability, by providing in many cases tight or almost tight bounds. Interestingly, the considered relaxed notions of core also possess the appealing property of recovering, in some notable cases, the convergence, the existence and the possibility of computing stable solutions in polynomial time.
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来源期刊
Artificial Intelligence
Artificial Intelligence 工程技术-计算机:人工智能
CiteScore
11.20
自引率
1.40%
发文量
118
审稿时长
8 months
期刊介绍: The Journal of Artificial Intelligence (AIJ) welcomes papers covering a broad spectrum of AI topics, including cognition, automated reasoning, computer vision, machine learning, and more. Papers should demonstrate advancements in AI and propose innovative approaches to AI problems. Additionally, the journal accepts papers describing AI applications, focusing on how new methods enhance performance rather than reiterating conventional approaches. In addition to regular papers, AIJ also accepts Research Notes, Research Field Reviews, Position Papers, Book Reviews, and summary papers on AI challenges and competitions.
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