NDLI: Multi-Population Agent Search: Stigmergy and Heterogeneity

Content Provider	IEEE Xplore Digital Library
Author	Chira, C. Pintea, C.-M. Dumitrescu, D.
Copyright Year	2008
Description	Author affiliation: Dept. of Comput. Sci., Babes-Bolyai Univ., Cluj-Napoca, Romania (Chira, C.; Pintea, C.-M.; Dumitrescu, D.)
Abstract	Ant systems normally rely on identical agents that cooperate indirectly using pheromone trails to find a problem solution. This uniformity may be inadequate in solving difficult problems where complex behavior patterns are needed. A new ant-based model is developed with the aim of promoting non-uniformity in the agent population by enhancing each agent with properties that induce heterogeneity. Agents are endowed with different pheromone sensitivity levels. Highly-sensitive agents are essentially influenced in the decision making process by stigmergic information and thus likely to select strong pheromone-marked moves. Agents with low sensitivity are biased towards random search inducing diversity for exploration. Sensitive agents allow many types of reactions to a changing environment facilitating an efficient balance between exploration and exploitation. This balance is pursued by organizing the agents in several subpopulations based on a sensitivity level interval. Therefore, each subpopulation has a specific behavior given by the sensitivity level spanning from the diversification to the intensification of the search. The proposed model is engaged in a set of numerical experiments and comparisons for solving various combinatorial optimization problems with very promising results.
Starting Page	526
Ending Page	531
File Size	234591
Page Count	6
File Format	PDF
ISBN	9780769535234
DOI	10.1109/SYNASC.2008.46
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-09-26
Publisher Place	Romania
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Ant colony optimization Scientific computing multi-agent search Decision making Scheduling Organizing heterogeneity Design optimization Computer science Algebra Storage automation sensitive ants Mathematical programming
Content Type	Text
Resource Type	Article

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