NDLI: Coadaptive behaviour in a simple distributed job scheduling system

Content Provider	IEEE Xplore Digital Library
Author	Glockner, A. Pasquale, J.
Copyright Year	1971
Abstract	A simple system that demonstrates coadaptation in distributed decision-making as applied to the problem of job scheduling is presented. The decision-making process is constructed as a set of autonomous agents based on learning automata that can individually learn from feedback. The set of agents adapt together, or coadapt, to form a good, though not necessarily optimal, global decision process. Coadaptive distributed computer job scheduling in a two-machine system is simulated with the agents implemented as stochastic learning automata. It is demonstrated that the performance of these coadaptive agents is similar to that of a related group of well-performing static decision-making agents, that quantitative changes in agents' parameters cause qualitative changes in the coadaptive behavior, and that constructing an optimal agent for a coadapting system is dependent upon the other agents present. Coadaptive behavior is clearly affected by the relative frequencies with which decisions are made, and relative sizes of the rewards and penalties.<>
Starting Page	902
Ending Page	907
Page Count	6
File Size	705796
File Format	PDF
ISSN	00189472
Volume Number	23
Issue Number	3
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1993-05-01
Publisher Place	U.S.A.
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Processor scheduling Decision making Learning automata Distributed decision making Autonomous agents Feedback Distributed computing Computational modeling Computer simulation Stochastic systems
Content Type	Text
Resource Type	Article
Subject	Engineering

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