The algorithmic beauty of plants
The algorithmic beauty of plants
Agent-organized networks for dynamic team formation
Proceedings of the fourth international joint conference on Autonomous agents and multiagent systems
Cooperative Multi-Agent Learning: The State of the Art
Autonomous Agents and Multi-Agent Systems
A survey of multi-agent organizational paradigms
The Knowledge Engineering Review
Local strategy learning in networked multi-agent team formation
Autonomous Agents and Multi-Agent Systems
| Hi-index | 0.00 |
In this paper we present a novel developmental, evolutionary approach for evolving scalable, hierarchical control structures for large (100-1000 agent), multi-agent swarms. Although hierarchical, the control structure does not suffer from single point of failures as do many hierarchical structures. The results show that for some problems using an evolved control hierarchy to guide the agents leads to significantly better performance and scaling properties than fully distributed swarms using standard behavioral rules.