Coordinated Learning by Model Difference Identification in Multiagent Systems with Sparse Interactions
Joint Authors
Yin, Quanjun
Jiao, Peng
Zhang, Qi
Sun, Lin
Source
Discrete Dynamics in Nature and Society
Issue
Vol. 2016, Issue 2016 (31 Dec. 2016), pp.1-17, 17 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2016-10-12
Country of Publication
Egypt
No. of Pages
17
Main Subjects
Abstract EN
Multiagent Reinforcement Learning (MARL) is a promising technique for agents learning effective coordinated policy in Multiagent Systems (MASs).
In many MASs, interactions between agents are usually sparse, and then a lot of MARL methods were devised for them.
These methods divide learning process into independent learning and joint learning in coordinated states to improve traditional joint state-action space learning.
However, most of those methods identify coordinated states based on assumptions about domain structure (e.g., dependencies) or agent (e.g., prior individual optimal policy and agent homogeneity).
Moreover, situations that current methods cannot deal with still exist.
In this paper, a modified approach is proposed to learn where and how to coordinate agents’ behaviors in more general MASs with sparse interactions.
Our approach introduces sample grouping and a more accurate metric of model difference degree to identify which states of other agents should be considered in coordinated states, without strong additional assumptions.
Experimental results show that the proposed approach outperforms its competitors by improving the average agent reward per step and works well in some broader scenarios.
American Psychological Association (APA)
Zhang, Qi& Jiao, Peng& Yin, Quanjun& Sun, Lin. 2016. Coordinated Learning by Model Difference Identification in Multiagent Systems with Sparse Interactions. Discrete Dynamics in Nature and Society،Vol. 2016, no. 2016, pp.1-17.
https://search.emarefa.net/detail/BIM-1103399
Modern Language Association (MLA)
Zhang, Qi…[et al.]. Coordinated Learning by Model Difference Identification in Multiagent Systems with Sparse Interactions. Discrete Dynamics in Nature and Society No. 2016 (2016), pp.1-17.
https://search.emarefa.net/detail/BIM-1103399
American Medical Association (AMA)
Zhang, Qi& Jiao, Peng& Yin, Quanjun& Sun, Lin. Coordinated Learning by Model Difference Identification in Multiagent Systems with Sparse Interactions. Discrete Dynamics in Nature and Society. 2016. Vol. 2016, no. 2016, pp.1-17.
https://search.emarefa.net/detail/BIM-1103399
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1103399