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Swarm intelligence: Novel tools for feature extraction and multi-agent system modeling
Aleksandar Jevtic
Technical University of Madrid
Department of Signals, Systems and Radiocommunications


Methods for the solution of difficult computational problems based on swarm intelligence have been experimentally demonstrated and reported in the literature. However, a general framework that would facilitate their design does not exist yet. We propose a new general design methodology for the development of swarm intelligence tools. By defining a discrete space in which the members of the swarm can move, and by modifying the rules of local interactions and setting the adequate objective function for solutions evaluation, we test the proposed methodology in various domains. The seminar will present a set of case studies, and will focus on two general approaches. One approach is to apply swarm intelligence as a tool for optimization and feature extraction, and the other approach is to model multi-agent systems such that they resemble swarms of animals in nature providing them with the ability to autonomously perform a task at hand.


image processing, cluster analysis, distributed task allocation, multi-agent systems, swarm robotics