Multi-agent programming contest 2017: BusyBeaver team description

Multi-agent programming contest 2017: BusyBeaver team description

This paper describes the team BusyBeaver, that participated in and won the Multi-Agent Programming Contest 2017. Its strategy is based on dividing agents into three static groups modeling the work chain of buying, assembling and delivering items. The team is coordinated by a centralized agent doing...

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Veröffentlicht in:Annals of mathematics and artificial intelligence 2018-10, Vol.84 (1-2), p.17-33
1. Verfasser: Pieper, Jonathan
Format: Artikel
Sprache:eng
Schlagworte:
Artificial Intelligence
Bids
Buying
Complex Systems
Computer Science
Contests
Cooperation
Greedy algorithms
Mathematics
Multiagent systems
Random variables
Simulation
Teams
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Zusammenfassung:This paper describes the team BusyBeaver, that participated in and won the Multi-Agent Programming Contest 2017. Its strategy is based on dividing agents into three static groups modeling the work chain of buying, assembling and delivering items. The team is coordinated by a centralized agent doing most of the high-level planning, usually using greedy algorithms and specialized heuristics. There is a heavy focus on proactively buying and assembling some items, in order to quickly complete upcoming jobs.
ISSN:1012-2443
1573-7470
DOI:10.1007/s10472-018-9589-7