Learning equilibrium as a generalization of learning to optimize

被引：1
|
作者：
Monderer, Dov [1 ]
Tennenholtz, Moshe [1 ]
机构：
[1] Technion Israel Inst Technol, Fac Ind Engn & Management, IL-32000 Haifa, Israel
来源：
ARTIFICIAL INTELLIGENCE | 2007年 / 171卷 / 07期
关键词：
learning; machine learning; learning equilibrium;
D O I：
10.1016/j.artint.2007.01.002
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
We argue that learning equilibrium is an appropriate generalization to multi-agent systems of the concept of learning to optimize in single-agent setting. We further define and discuss the concept of weak learning equilibrium. (c) 2007 Elsevier B.V. All rights reserved.
引用
收藏
页码：448 / 452
页数：5
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