Social learning in a simple task allocation game
Populations and Evolution
2017-02-21 v1 Multiagent Systems
Abstract
We investigate the effects of social interactions in task al- location using Evolutionary Game Theory (EGT). We propose a simple task-allocation game and study how different learning mechanisms can give rise to specialised and non- specialised colonies under different ecological conditions. By combining agent-based simulations and adaptive dynamics we show that social learning can result in colonies of generalists or specialists, depending on ecological parameters. Agent-based simulations further show that learning dynamics play a crucial role in task allocation. In particular, introspective individual learning readily favours the emergence of specialists, while a process resembling task recruitment favours the emergence of generalists.
Cite
@article{arxiv.1702.05739,
title = {Social learning in a simple task allocation game},
author = {Rui Chen and Garcia Julian and Meyer Bernd},
journal= {arXiv preprint arXiv:1702.05739},
year = {2017}
}