Signal-Driven Swarming: Evolution of Coordinated Motion in Groups of Embodied Agents
From biological cells to bee swarms and bird flocks, nature shows countless examples of self-organized groups displaying a collective mind. In such species, individuals interacting together end up producing an emergent behavior that increases their chances of survival and reproduction. We constructed a model first to study swarming behavior based on local interactions [Witkowski & Ikegami 2013, 2016] [Drozd, Witkowski et al. 2015], and secondly to analyze the advantages of such behavior when the agents are playing a spatial n-player Prisoner’s Dilemma [Witkowski et al. 2013]. Our results show the dynamics and stability of emergent collective strategies in nature and society.
Evolution of Coordination and Communication in Groups of Embodied Agents
In this project, we showed the influence of honest signaling for evolutionary stable strategies in variable environments, with results on synchronization with resource availability functions [Witkowski et al. 2012], resource-saving strategies [Witkowski & Aubert 2012] and the transmission of migratory behaviors [Witkowski & Nitschke 2013].
Reynolds’ Boids Swarming Behavior Evolved in Artificial Neural Networks
Gene-Culture Coevolution: A Model of Language Evolution via Relaxation of Selection
In this project, we used a agent-based model approach to study the evolution of fully- fledged languages, specifically focusing on gene-culture coevolution and the Baldwin effect [McCrohon & Witkowski 2011]. Our results showed interesting transition effects due to local attractors and population size.