# Emotional Metaheuristics For in-situ Foraging Using Sensor Constrained Robot Swarms

## TL;DR

This paper introduces an emotional swarm intelligence method inspired by social animals, enabling sensor-constrained robot swarms to effectively perform in-situ foraging through emergent collective behavior.

## Contribution

It presents a novel emotional-based interaction model for robot swarms that improves collective foraging capabilities in sensor-limited conditions.

## Key findings

- Emergent behavior enables effective foraging in sensor-constrained robots.
- Simple sensation-based rules lead to coherent group behavior.
- Simulation results demonstrate the approach's viability.

## Abstract

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