NDLI: Computational chemotaxis in ants and bacteria over dynamic environments

Content Provider	IEEE Xplore Digital Library
Author	Ramos, V. Fernandes, C. Rosa, A.C. Abraham, A.
Copyright Year	2007
Description	Author affiliation: 1ST - Tech. Univ. of Lisbon, Lisbon (Ramos, V.; Fernandes, C.; Rosa, A.C.)
Abstract	Chemotaxis can be defined as an innate behavioural response by an organism to a directional stimulus, in which bacteria, and other single-cell or multicellular organisms direct their movements according to certain chemicals in their environment This is important for bacteria to find food (e.g., glucose) by swimming towards the highest concentration of food molecules, or to flee from poisons. Based on self-organized computational approaches and similar stigmergic concepts we derive a novel swarm intelligent algorithm. What strikes from these observations is that both eusocial insects as ant colonies and bacteria have similar natural mechanisms based on stigmergy in order to emerge coherent and sophisticated patterns of global collective behaviour. Keeping in mind the above characteristics we will present a simple model to tackle the collective adaptation of a social swarm based on real ant colony behaviors (SSA algorithm) for tracking extrema in dynamic environments and highly multimodal complex functions described in the well-know Dejong test suite. Then, for the purpose of comparison, a recent model of artificial bacterial foraging (BFOA algorithm) based on similar stigmergic features is described and analyzed. Final results indicate that the SSA collective intelligence is able to cope and quickly adapt to unforeseen situations even when over the same cooperative foraging period, the community is requested to deal with two different and contradictory purposes, while outperforming BFOA in adaptive speed. Results indicate that the present approach deals well in severe Dynamic Optimization problems.
Starting Page	1109
Ending Page	1117
File Size	1061972
Page Count	9
File Format	PDF
ISBN	9781424413393
DOI	10.1109/CEC.2007.4424594
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2007-09-25
Publisher Place	Singapore
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Microorganisms Organisms Chemicals Sugar Toxicology Computational intelligence Particle swarm optimization Insects Testing Algorithm design and analysis Distributed Search and optimization in Dynamic Environments Swarm Intelligence and Perception Social Cognitive Maps Social Foraging Self-Organization
Content Type	Text
Resource Type	Article

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