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Research . 2018
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Research . 2018
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Research . 2018
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Other literature type . 2018
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https://dx.doi.org/10.5281/zen...
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Learning Complex Group Behaviors in a Multi-Agent Competitive Environment

descriptionPublicationkeyboard_double_arrow_right Research , Other literature type 28 Dec 2018 English Publisher:Zenodo
Authors: Sanlav; Nabi;

doi: 10.5281/zenodo.2528544 , 10.5281/zenodo.2528536 , 10.5281/zenodo.2528537

Learning Complex Group Behaviors in a Multi-Agent Competitive Environment

Abstract

The aim of this project is to use reinforcement learning algorithms to explore predator-prey dynamics, such as those seen when predator fish and prey fish interact in nature. In order to do so, we trained 2 competitive groups of agents using some reinforcement learning algorithms.

Keywords

multi-agent reinforcement learning

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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