文章基本信息

标题：Cooperative Problem Solving against Adversary: Quantified Distributed Constraint Satisfaction Problem
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作者：Satomi Baba ; Atsushi Iwasaki ; Makoto Yokoo 等
期刊名称：人工知能学会論文誌
印刷版ISSN：1346-0714
电子版ISSN：1346-8030
出版年度：2011
卷号：26
期号：1
页码：136-146
DOI：10.1527/tjsai.26.136
出版社：The Japanese Society for Artificial Intelligence
摘要：In this paper, we extend the traditional formalization of distributed constraint satisfaction problems (DisCSP) to a quantified DisCSP. A quantified DisCSP includes several universally quantified variables, while all of the variables in a traditional DisCSP are existentially quantified. A universally quantified variable represents a choice of nature or an adversary. A quantified DisCSP formalizes a situation where a team of agents is trying to make a robust plan against nature or an adversary. In this paper, we present the formalization of such a quantified DisCSP and develop an algorithm for solving it by generalizing the asynchronous backtracking algorithm used for solving a DisCSP. In this algorithm, agents communicate a value assignment called a good in addition to the nogood used in asynchronous backtracking. Interestingly, the procedures executed by an adversarial/cooperative agent for good / nogood are completely symmetrical. Furthermore, we develop a method that improves this basic algorithm. Experimental evaluation results illustrate that we observe an easy-hard-easy transition by changing the tightness of the constraints, while very loose problem instances are relatively hard. The modification of the basic algorithm is also effective and reduces the number of cycles by approximately 25% for the hardest problem instances.
关键词：distributed constraint satisfaction problem ; quantified constraint satisfaction problem