Chaotic dynamic characteristics in swarm intelligence

@article{citeulike:2897890, abstract = {Swarm intelligence (SI) is an innovative distributed intelligent paradigm whereby the collective behaviors of unsophisticated individuals interacting locally with their environment cause coherent functional global patterns to emerge. The intelligence emerges from a chaotic balance between individuality and sociality. The chaotic balances are a characteristic feature of the complex system. This paper investigates the chaotic dynamic characteristics in swarm intelligence. The swarm intelligent model namely the particle swarm (PS) is represented as an iterated function system (IFS). The dynamic trajectory of the particle is sensitive on the parameter values of IFS. The Lyapunov exponent and the correlation dimension are calculated and analyzed numerically for the dynamic system. Our research results illustrate that the performance of the swarm intelligent model depends on the sign of the maximum Lyapunov exponent. The particle swarm with a high maximum Lyapunov exponent usually achieves better performance, especially for multi-modal functions.}, author = {Liu, Hongbo and Abraham, Ajith and Clerc, Maurice }, citeulike-article-id = {2897890}, doi = {http://dx.doi.org/10.1016/j.asoc.2006.10.006}, journal = {Applied Soft Computing}, month = {June}, number = {3}, pages = {1019--1026}, posted-at = {2008-06-16 09:34:11}, priority = {0}, title = {Chaotic dynamic characteristics in swarm intelligence}, url = {http://dx.doi.org/10.1016/j.asoc.2006.10.006}, volume = {7}, year = {2007} }

TY - JOUR ID - citeulike:2897890 L3 - citeulike-article-id:2897890 TI - Chaotic dynamic characteristics in swarm intelligence JF - Applied Soft Computing VL - 7 IS - 3 SP - 1019 EP - 1026 N2 - Swarm intelligence (SI) is an innovative distributed intelligent paradigm whereby the collective behaviors of unsophisticated individuals interacting locally with their environment cause coherent functional global patterns to emerge. The intelligence emerges from a chaotic balance between individuality and sociality. The chaotic balances are a characteristic feature of the complex system. This paper investigates the chaotic dynamic characteristics in swarm intelligence. The swarm intelligent model namely the particle swarm (PS) is represented as an iterated function system (IFS). The dynamic trajectory of the particle is sensitive on the parameter values of IFS. The Lyapunov exponent and the correlation dimension are calculated and analyzed numerically for the dynamic system. Our research results illustrate that the performance of the swarm intelligent model depends on the sign of the maximum Lyapunov exponent. The particle swarm with a high maximum Lyapunov exponent usually achieves better performance, especially for multi-modal functions. AU - Liu, Hongbo AU - Abraham, Ajith AU - Clerc, Maurice PY - 2007/06// UR - http://dx.doi.org/10.1016/j.asoc.2006.10.006 ER -