Emotional Metaheuristics For in-situ Foraging Using Sensor Constrained Robot Swarms
This addresses the challenge of enabling robot swarms with limited sensors to perform collective tasks like foraging, though it appears incremental as it builds on existing swarm intelligence methods.
The authors tackled the problem of foraging with sensor-constrained robot swarms by developing an emotional swarm intelligence technique inspired by social animals, and they demonstrated through simulation that simple rules based on hunger and loneliness lead to globally coherent emergent behavior.
We present a new social animal inspired emotional swarm intelligence technique. This technique is used to solve a variant of the popular collective robots problem called foraging. We show with a simulation study how simple interaction rules based on sensations like hunger and loneliness can lead to globally coherent emergent behavior which allows sensor constrained robots to solve the given problem