H. David Mathias
Annie S. Wu
ABSTRACT
In this work, we use a multiobjective genetic algorithm to evolve agent response thresholds for a decentralized swarm and demonstrate that swarms with evolved thresholds outperform swarms with thresholds set using other methods. In addition, we provide evidence that the effectiveness of evolved thresholds is due in part to the evolutionary process being able to find, not just good distributions of thresholds for a given task across all agents, but also good combinations of thresholds over all tasks for individual agents. Finally, we show that thresholds evolved for some problem instances can effectively generalize to other problem instances with very different task demands.
- Annie S. Wu, H. David Mathias, Joseph P. Giordano, and Arjun Pherwani. 2021. Collective control as a decentralized task allocation testbed. Technical Report CS-TR-21-01. University of Central Florida.Google Scholar
Index Terms
- Evolved response thresholds generalize across problem instances for a deterministic-response multiagent system
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