DocumentCode :
2967932
Title :
Multi-Population Agent Search: Stigmergy and Heterogeneity
Author :
Chira, Camelia ; Pintea, Camelia M. ; Dumitrescu, D.
Author_Institution :
Dept. of Comput. Sci., Babes-Bolyai Univ., Cluj-Napoca, Romania
fYear :
2008
fDate :
26-29 Sept. 2008
Firstpage :
526
Lastpage :
531
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.
Keywords :
combinatorial mathematics; multi-agent systems; optimisation; ant systems; ant-based model; combinatorial optimization problems; complex behavior patterns; decision making process; heterogeneity; identical agents; multi-population agent search; pheromone trails; sensitive agents; stigmergic information; stigmergy; Algebra; Ant colony optimization; Computer science; Decision making; Design optimization; Mathematical programming; Organizing; Scheduling; Scientific computing; Storage automation; heterogeneity; multi-agent search; sensitive ants;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Symbolic and Numeric Algorithms for Scientific Computing, 2008. SYNASC '08. 10th International Symposium on
Conference_Location :
Timisoara
Print_ISBN :
978-0-7695-3523-4
Type :
conf
DOI :
10.1109/SYNASC.2008.46
Filename :
5204865
Link To Document :
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