Numerical recipes in C (2nd ed.): the art of scientific computing
Numerical recipes in C (2nd ed.): the art of scientific computing
Swarm intelligence: from natural to artificial systems
Swarm intelligence: from natural to artificial systems
Stigmergy, self-organization, and sorting in collective robotics
Artificial Life
Computer methods for sampling from the exponential and normal distributions
Communications of the ACM
Self-Organization in Biological Systems
Self-Organization in Biological Systems
Division of labor in a group of robots inspired by ants' foraging behavior
ACM Transactions on Autonomous and Adaptive Systems (TAAS)
Swarm robotics: from sources of inspiration to domains of application
SAB'04 Proceedings of the 2004 international conference on Swarm Robotics
Self-Organized Coordinated Motion in Groups of Physically Connected Robots
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Opinion dynamics for decentralized decision-making in a robot swarm
ANTS'10 Proceedings of the 7th international conference on Swarm intelligence
Biologically inspired collective comparisons by robotic swarms
International Journal of Robotics Research
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Self-amplification processes are at the origin of several collective decision phenomena in insect societies. Understanding these processes requires linking individual behavioral rules of insects to a choice dynamics at the colony level. In a homogeneous environment, the German cockroach Blattella germanica displays self-amplified aggregation behavior. In a heterogeneous environment where several shelters are present, groups of cockroaches collectively select one of them. In this article, we demonstrate that the restriction of the self-amplified aggregation behavior to distinct zones in the environment can explain the emergence of a collective decision at the level of the group. This hypothesis is tested with robotics experiments and dedicated computer simulations. We show that the collective decision is influenced by the available spaces to explore and to aggregate in, by the size of the population involved in the aggregation process and by the probability of encounter zones while the robots explore the environment. We finally discuss these results from both a biological and a robotics point of view.