NDLI: Immune algorithm with immune network and MHC for adaptive problem solving

Content Provider	IEEE Xplore Digital Library
Author	Toma, N. Endo, S. Yamanda, K.
Copyright Year	1999
Description	Author affiliation: Graduade Sch. of Sci. & Eng., Ryukyus Univ., Okinawa, Japan (Toma, N.)
Abstract	Adaptive problem solving techniques such as neural networks and genetic algorithms become so popular in the AI field. The biological immune system is one of the adaptive biological systems whose functions are to identify and to eliminate foreign materials. In this paper, we propose an adaptive optimization algorithm based on immune model with immune network and major histocompatibility complex (MHC). In biological immune system, immune network controls immune responses by changing its structure. The MHC is used to distinguish a "self" from other "not self". In our model, immune network is used to produce adaptive behaviors of agents, which are computing subject for problem solving. MHC is used to induce competitive behaviors among agents. To investigate an adaptation ability of the proposed algorithm, we apply it to the n-th agent's travelling salesman problem called n-TSP. This algorithm performs adaptive behaviors for distributed cooperation.
Starting Page	271
Ending Page	276
File Size	472092
Page Count	6
File Format	PDF
ISBN	0780357310
ISSN	1062922X
DOI	10.1109/ICSMC.1999.812412
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1999-10-12
Publisher Place	Japan
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Immune system Problem-solving Biological system modeling Neural networks Genetic algorithms Artificial intelligence Adaptive systems Biological systems Biological materials Biological control systems
Content Type	Text
Resource Type	Article

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