2019/03/19 by Olaf Witkowski, Takashi Ikegami, Witkowski, Olaf +1
Computer Science · Engineering · Physics and Astronomy · Social Sciences · #Adaptation and Self-Organizing Systems (nlin.AO) #Cellular Automata and Applications #Distributed #Evolutionary Game Theory and Cooperation #FOS: Computer and information sciences #FOS: Physical sciences #Modular Robots and Swarm Intelligence #Multiagent Systems (cs.MA) #Neural and Evolutionary Computing (cs.NE) #Parallel #and Cluster Computing (cs.DC) #cs.DC #cs.MA #cs.NE #nlin.AO
paper · pdf · doi:10.48550/arxiv.1903.08228
40 pages, 7 figures
arxiv created 2019/03/19 · openalex publication_date 2019/03/19 · arxiv updated 2019/03/21 · openalex created_date 2019/04/01 · openalex updated_date 2026/07/28
We propose an approach of open-ended evolution via the simulation of swarm dynamics. In nature, swarms possess remarkable properties, which allow many organisms, from swarming bacteria to ants and flocking birds, to form higher-order structures that enhance their behavior as a group. Swarm simulations highlight three important factors to create novelty and diversity: (a) communication generates combinatorial cooperative dynamics, (b) concurrency allows for separation of timescales, and (c) complexity and size increases push the system towards transitions in innovation. We illustrate these three components in a model computing the continuous evolution of a swarm of agents. The results, divided in three distinct applications, show how emergent structures are capable of filtering information through the bottleneck of their memory, to produce meaningful novelty and diversity within their simulated environment.