NDLI: Localization for a class of two-team zero-sum Markov games

Content Provider	IEEE Xplore Digital Library
Author	Hyeong Soo Chang Fu, M.C.
Copyright Year	2004
Description	Author affiliation: Dept. of Comput. Sci. & Eng., Sogang Univ., Seoul, South Korea (Hyeong Soo Chang)
Abstract	This paper presents a novel concept of "localization" for a class of infinite horizon two-team zero-sum Markov games (MGs) with a minimizer team of multiple decision makers that competes against nature (a maximizer team) which controls the disturbances that are unknown to the minimizer team. The minimizer team is associated with a general joint cost structure but has a special decomposable state/action structure such that each pair of a minimizing agent's action and a random disturbance to the agent affects the system's state transitions independently from all of the other pairs. By localization, the original MG is decomposed into "local" MGs defined only on local state and action spaces. We discuss how to use localization to develop an efficient distributed heuristic scheme to find an "autonomous" joint policy such that each agent's action is based on only its local state.
Starting Page	4844
Ending Page	4849
File Size	189570
Page Count	6
File Format	PDF
ISBN	0780386825
ISSN	01912216
DOI	10.1109/CDC.2004.1429563
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2004-12-14
Publisher Place	Bahamas
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Cost function Game theory Computer science Educational institutions Infinite horizon Control systems Decision making Uncertainty Robust control Protocols
Content Type	Text
Resource Type	Article

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