NEURAL NETWORKS AS SOURCES OF CHAOTIC MOTOR ACTIVITY IN ANTS AND HOW COMPLEXITY DEVELOPS AT THE SOCIAL SCALE

Autor:	Ricard V. Solé, Octavio Miramontes, Brian C. Goodwin
Rok vydání:	2001
Předmět:	Artificial neural network business.industry Applied Mathematics Chaotic Process (computing) Scale (descriptive set theory) Ant colony Measure (mathematics) Iterated function system Modeling and Simulation Motor activity Artificial intelligence business Engineering (miscellaneous) Mathematics
Zdroj:	International Journal of Bifurcation and Chaos. 11:1655-1664
ISSN:	1793-6551 0218-1274
DOI:	10.1142/s0218127401002912
Popis:	We discuss a Neural Network model generating activation signals for locomotion in ants. The signals are chaotic and so are the temporal patterns of spontaneous activations in single ants. Active ants are able to move and interact with other nest mates. This process of movement-interaction generates periodic pulses of activity once the number of individuals reaches a certain density value. An algorithmic complexity measure is used for identifying accurately the transition from chaos into order. Finally, an Iterated Function System analysis reveals the richness of dynamical behavior that emerges when ant colonies are self-poised near such a transition.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::80b2c1ba0d81ca153359d7339be43696 https://doi.org/10.1142/s0218127401002912 Zobrazit plný text záznamu