Affordable Access

Towards dynamic adaptation of the majority rule scheme

Authors
Publisher
Sapienza Università di Roma
Publication Date
Disciplines
  • Computer Science
  • Economics

Abstract

Submitted to: QAPL 2013 Towards Dynamic Adaptation of the Majority Rule Scheme C. Krause Department of System Analysis and Modeling, Hasso Plattner Institute for Software Systems Engineering E.P. de Vink∗ Department of Mathematics and Computer Science, Technische Universiteit Eindhoven Centrum Wiskunde en Informatica, Amsterdam P.J. de Vink Faculty of Science, University of Amsterdam Abstract The majority rule scheme has been applied in the setting of robot swarms as a mechanism to reach consensus among a population of robots regarding the optimality of one out of two options. In the context of distributed decision making for agents, we consider two schemes of combining the majority rule scheme with dynamic adaptation for the well-known double bridge problem to cater for a situation where the shortest path changes over time. By modeling the systems as Markov chains, initial results regarding the quality and the trade-off of efficiency and adaptation time can be obtained. 1 Introduction Distributed decision making by collectives of autonomous agents ultimately relies on the available inter- action schemes. For populations of ants it is well-known that by means of pheromones ants can select the shortest of two paths leading from the nest to a place with food. Since pheromones evaporate over time the shortest path is indicated more strongly than the longer one. For robots swarms no satisfactory physical counterpart of pheromones has been agreed upon yet. In [5] Montes de Oca et al. propose the mechanism of the majority rule –as studied in sociology, economics and physics– as a computational alternative. The approach has been developed for swarms of autonomous robots in a static environment where the aim is to reach consensus among all robots on which one out of two paths is the shortest. Generally, distributed decision making assumes a static environment. However, ants are very well capable to reconsider their preferences in a changing environment. In a variation of t

There are no comments yet on this publication. Be the first to share your thoughts.