Solitary Intelligence

Swarm Intelligence has become a popular and active area of research for formulating various optimisation techniques which draw ideas from the swarms existing in nature. These techniques tend to produce very effective and efficient solutions to such problems and thus have gained popularity because of their flexibility and versatility. Swarm Intelligence covers a wide variety of animals and insects found in nature which work in a group. We have observed that agents in a few of these techniques work individually. So, in this paper we introduce a new class of nature inspired algorithms called Solitary Intelligence which draws its inspiration from intelligent behaviour of natural agents who work alone.

[1]  Janice I. Glasgow,et al.  Swarm Intelligence: Concepts, Models and Applications , 2012 .

[2]  Mauro Birattari,et al.  Swarm Intelligence , 2012, Lecture Notes in Computer Science.

[3]  Yue Shi,et al.  A modified particle swarm optimizer , 1998, 1998 IEEE International Conference on Evolutionary Computation Proceedings. IEEE World Congress on Computational Intelligence (Cat. No.98TH8360).

[4]  Donald E. Grierson,et al.  Comparison among five evolutionary-based optimization algorithms , 2005, Adv. Eng. Informatics.

[5]  Xin-She Yang,et al.  Cuckoo Search via Lévy flights , 2009, 2009 World Congress on Nature & Biologically Inspired Computing (NaBIC).

[6]  Ajith Abraham,et al.  Taxonomy of nature inspired computational intelligence: A remote sensing perspective , 2012, 2012 Fourth World Congress on Nature and Biologically Inspired Computing (NaBIC).

[7]  Xin-She Yang,et al.  Nature-Inspired Metaheuristic Algorithms , 2008 .

[8]  Riccardo Poli,et al.  Particle Swarm Optimisation , 2011 .

[9]  Marco Dorigo,et al.  Ant algorithms and stigmergy , 2000, Future Gener. Comput. Syst..

[10]  J. Altringham.  Bats: Biology and Behaviour , 1996 .

[11]  Ajith Abraham,et al.  Swarm Intelligence in Data Mining , 2009, Swarm Intelligence in Data Mining.

[12]  Xin-She Yang,et al.  A New Metaheuristic Bat-Inspired Algorithm , 2010, NICSO.

[13]  Dervis Karaboga,et al.  AN IDEA BASED ON HONEY BEE SWARM FOR NUMERICAL OPTIMIZATION , 2005 .

[14]  Tom Fearn,et al.  Particle Swarm Optimisation , 2014 .

[15]  Marco Dorigo,et al.  Ant system: optimization by a colony of cooperating agents , 1996, IEEE Trans. Syst. Man Cybern. Part B.

[16]  S. Arora,et al.  A conceptual comparison of firefly algorithm, bat algorithm and cuckoo search , 2013, 2013 International Conference on Control, Computing, Communication and Materials (ICCCCM).