Individual and Social Behaviour in the IPA Market with RL

被引:0
|
作者
Gomes, Eduardo Rodrigues [1 ]
Kowalczyk, Ryszard [1 ]
机构
[1] Swinburne Univ Technol, Fac Informat & Commun Technol, Hawthorn, Vic 3122, Australia
来源
ADVANCES IN ARTIFICIAL INTELLIGENCE - SBIA 2008, PROCEEDINGS | 2008年 / 5249卷
关键词
Market-based Resource Allocation; Reinforcement Learning; Multiagent Systems;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Market-based mechanisms offer a promising approach for distributed resource allocation. Machine Learning been proposed to influence and optimize market-based resource allocation. In particular, Reinforcement Learning (RL) has been used to improve the allocation in terms of utility received by resource requesting agents in the Iterative Price Adjustment (IPA) mechanism. This paper analyses the individual and social behaviour of agents in the IPA market-based resource allocation with RL. In particular: it presents results of experimental investigation on the influences of the amount of learning in the agents behaviour aiming at determining how much learning is sufficient and the theoretical-experimental explanation of the agent's behaviours using game theory. game theory.
引用
收藏
页码:93 / 102
页数:10
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