Self-organized sorting limits behavioral variability in swarms

Global-to-Local Design for Self-Organized Task Allocation in Swarms

We propose a global-to-local design methodology to compose heterogeneous swarms for self-organized task allocation. We consider embodied agents with only local knowledge and local communication driven by a simple reactive-control architecture (i.e., local level). We define finitely many agent controllers and focus on the macroscopic dynamics (i.e., global level) of behaviorally heterogeneous sw...

Conformity and Nonconformity in Collective Robotics: A Case Study

In this work, we develop a social behavioral model designed for multi-agent systems for solving the collective sorting task. Experiments show that under this model agents are capable of improving their performance significantly and can achieve better results than conventional swarms of agents lacking communication and social abilities.

Self Organized Multi Agent Swarms (SOMAS) for Network Security Control THESIS

An Approach to Sorting Swarm Robots to Optimize Performance

Swarm robotic systems can offer many advantages including robustness, flexibility and scalability. However one of the issues relating to overall swarm performance that needs to be considered is hardware variations inherent in the implementation of individual swarm robots. This variation can bring behavioral diversity within the swarm, resulting in uncontrollable swarm behaviors, low efficiency,...

Correction: Evolution of Self-Organized Task Specialization in Robot Swarms

Division of labor is ubiquitous in biological systems, as evidenced by various forms of complex task specialization observed in both animal societies and multicellular organisms. Although clearly adaptive, the way in which division of labor first evolved remains enigmatic, as it requires the simultaneous co-occurrence of several complex traits to achieve the required degree of coordination. Rec...