If multi-agent learning is the answer, what is the question?

被引：175

作者：

Shoham, Yoav ^{[1
]}

Powers, Rob ^{[1
]}

Grenager, Trond ^{[1
]}

机构：

[1] Stanford Univ, Dept Comp Sci, Stanford, CA 94305 USA

来源：

ARTIFICIAL INTELLIGENCE | 2007年 / 171卷 / 07期

基金：

美国国家科学基金会;

关键词：

D O I：

10.1016/j.artint.2006.02.006

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

The area of learning in multi-agent systems is today one of the most fertile grounds for interaction between game theory and artificial intelligence. We focus on the foundational questions in this interdisciplinary area, and identify several distinct agendas that ought to, we argue, be separated. The goal of this article is to start a discussion in the research community that will result in firmer foundations for the area(1). (c) 2007 Published by Elsevier B.V.

引用

页码：365 / 377

页数：13

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