Achieving Consensus in Robot Swarms by Gabriele Valentini

By Gabriele Valentini

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In the second case, environmental bias factors influence negatively the option quality and the decision-making problem requires a compromise between option quality and cost. The taxonomy illustrated in Fig. 4 provides us with different means to interpret the swarm robotics literature. We conclude this chapter by reorganizing the research studies reviewed in Sects. 1. 1 Classification of the swarm robotics literature according to the combination of factors that determines the quality of the options of the best-of-n problem Internal preference Environmental bias Research lines/studies No No Yes Yes No Yes, positive bias Yes, negative bias i.

2 Modular Perspective of a Strategy Dissemination state: 39 E1 En Ei Broadcast( i ) Listen( ) ∀j < i i = Decision( ) DR D1 ∀j > i DR DR Di Dn Fig. 5 Illustration of the control-flow followed by an agent in the dissemination state Di . Routines “Broadcast()”, “Listen()”, and “Decision()” are used to disseminate opinion i, to listen to the neighbors’ opinions, and to reconsider the agent’s opinion dissemination state Di and transits to the exploration state E j corresponding to its new opinion. , routine “Broadcast()”, routine “Listen()”, and routine “Decision()” in Fig.

Appl. 281(1–4), 17–29 (2000) A. -L. Barabási, T. Vicsek, Collective motion of self-propelled particles: kinetic phase transition in one dimension. Phys. Rev. Lett. 82, 209–212 (1999) H. C. Biesmeijer, Self-organization in collective honeybee foraging: emergence of symmetry breaking, cross inhibition and equal harvest-rate distribution. Behav. Ecol. Sociobiol. -L. Deneubourg, S. Goss, Collective patterns and decision-making. Ethol. Ecol. Evol. 1(4), 295– 311 (1989) E. Ferrante, Information transfer in a flocking robot swarm.

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