Agents Displacement in Arbitrary Geometrical Spaces - An Evolutionary Computation based Approach

Abstract

Abstract:In many different social contexts, communication allows a collective intelligence to emerge. However, a correct way of exchanging information usually requires determined topological configurations of the agents involved in the process. Such a configuration should take into account several parameters, e.g. agents positioning, their proximity and time efficiency of communication. Our aim is to present an algorithm, based on evolutionary programming, which optimizes agents placement on arbitrarily shaped areas. In order to show its ability to deal with arbitrary bi-dimensional topologies, this algorithm has been tested on a set of differently shaped areas that present concavities, convexities and obstacles. This approach can be extended to deal with concrete cases, such as object localization in a delimited area.

Towards the Improvement of Citizen Communication Through Computational Intelligence

“…[11,13,23]). Many such methodologies, especially the ones from the tradition of soft computing (metaheuristics, fuzzy systems), are in fact a natural match for cognition, as they are based on the fundamental idea that human cognition as a process is not based on symbol manipulation using strict rules, but has evolved to take into account a reality whose sheer complexity rapidly becomes intractable if not by acknowledging a constant selection of information, the uncertain nature of communication, and subjective probability as a rule of behaviour.…”