Showing papers on "Swarm intelligence published in 1992"

Self-organization of sensors for swarm intelligence

Abstract: The realization of sensing swarms composed of value-specific sensing elements requires distributed cooperation among the members of the swarm. The number of value-specific sensing elements must change under changing external conditions. The recalculations of the optimal distribution of sensing elements can be carried out from the knowledge of the (changed) average value of the sensed feature. Mathematically this can be done by using the maximum-entropy principle. However, distribution operation requires solving two additional problems: the new average value must be known to each sensing element, and a new configuration must be achieved autonomously (i.e. under distributed control). For the solution to these problems the authors introduce a circulating swarm model in which the elements of the swarm circulate in a ring while performing the sensing operations and the self-organization. They show which elementary operations can be used in an algorithm for self-organization of the swarm in a new configuration optimized for sensing. >

Self organizing behavior and swarm intelligence in a cellular robotic system

Abstract: The authors describe the notion of a distributed robotic system (DRS) based on instinctive response and cooperation. Two specific aspects of the DRS are investigated in some detail: the self-configuration capabilities and the pattern generation problem. Simulation was used as a tool for dealing with the variety of possible distributions of the DRS, of environmental conditions, and of individual reactions of each robotic unit. Problems associated with communication between robotic units are also addressed. Simulation results demonstrate that communication and cooperation are very effective in enhancing the performance of the DRS during tasks requiring exploration, such as the search for pollutants. >

On formal constraints in swarm dynamics

Abstract: The authors deal with distributed problem solving in social insect colonies. They show that different processes used by social insects could be implemented in artificial swarm systems to solve different categories of problems. After reviewing these problems and defining some basic concepts of swarm intelligence they examine through the example of building behavior in termite and wasp colonies how different types of constraints operate both on individual behavior and on swarm dynamics. >