Inter-Agent Variation Improves Dynamic Decentralized Task Allocation
Abstract
We examine the effects of inter-agent variation on the ability of a decentralized multi-agent system (MAS) to self-organize in response to dynamically changing task demands. In decentralized biological systems, inter-agent variation as minor as noise has been observed to improve a system's ability to redistribute agent resources in response to external stimuli. We compare the performance of two MAS consisting of agents with and without noisy sensors on a cooperative tracking problem and examine the effects of inter-agent variation on agent behaviors and how those behaviors affect system performance. Results show that small variations in how individual agents respond to stimuli can lead to more accurate and stable allocation of agent resources.
Publication Date
1-1-2018
Publication Title
Proceedings of the 31st International Florida Artificial Intelligence Research Society Conference, FLAIRS 2018
Number of Pages
366-369
Document Type
Article; Proceedings Paper
Personal Identifier
scopus
Copyright Status
Unknown
Socpus ID
85071914762 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/85071914762
STARS Citation
Wu, Annie S. and Riggs, Cortney, "Inter-Agent Variation Improves Dynamic Decentralized Task Allocation" (2018). Scopus Export 2015-2019. 10057.
https://stars.library.ucf.edu/scopus2015/10057