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Abstract. Swarm intelligence is an important concept in artificial intelligence and com- puter science with emergent properties. The essential idea of swarm intelligence algorithms is to employ many simple agents applying almost no rule which in turn leads to an emergent global behavior. In this paper, we will introduce
Swarm Intelligence and Ant Colony. Optimisation. EXTRA READING: Swarm Intelligence by Eberhart et al, Morgan Kaufmann. Swarm Intelligence, From Natural to Artificial Systems by Bonabeau, Dorigo,. Theraulaz, Oxford University Press. Papers: A Simplified Recombinant PSO. Ant colonies for the traveling salesman
Swarm Intelligence: Literature Overview. Yang Liu and Kevin M. Passino. Dept. of Electrical Engineering. The Ohio State University. 2015 Neil Ave. Columbus, OH 43210. Tel: (614)292-5716, fax: (614)292-7596. Email: liuya@ee.eng.ohio-state.edu, passino@ee.eng.ohio-state.edu. March 30, 2000
Swarm intelligence was originally used in the context of cellular robotic systems to describe the self-organization of simple mechanical agents through nearest-neighbor interaction. 0 It was later extended to include “any attempt to design algorithms or distributed problem-solving devices inspired by the collective behavior
In this chapter we focus on swarm intelligence methods for solving optimization and search problems. The two main areas of swarm intel- ligence that are relevant for such problems are ant colony optimization. (ACO) and particle swarm optimization (PSO). ACO is a metaheuristic for solving combinatorial optimization prob-.
Swarm Intelligence. Companion slides for the book Bio-Inspired Artificial Intelligence: Theories,. Methods, and Technologies by Dario Floreano and Claudio Mattiussi, MIT Press. 1
Full-text (PDF) | Nature has always been a rich inspirational source over the ages, with much still to learn from and discover about. Swarm Intelligence (SI) is a relatively new and potentially promising branch of Artificial Intelligence that is used to model the collective intelligent behavior of
Increasing numbers of books, websites and articles are devoted to the concept of. 'swarm intelligence'. Meanwhile, a perhaps confusing variety of computational techniques are seen to be associated with this term, such as 'agents', 'emergence',. 'boids', 'ant colony optimisation', and so forth. In this chapter we attempt to.
Why is Swarm Intelligence interesting for IT? Analogies in IT and social insects distributed system of interacting autonomus agents goals: performance optimization and robustness self-organized control and cooperation (decentralized) division of labour and distributed task allocation indirect interactions
Swarm Intelligence: Concepts, Models and Applications. Technical Report 2012-585. Hazem Ahmed. Janice Glasgow. School of Computing. Queen's University. Kingston, Ontario, Canada K7L3N6. {hazem, janice}@cs.queensu.ca. February 2012

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