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• W2913103105 abstract "Learning in multi-agent scenarios is a fruitful research direction, but current approaches still show scalability problems in multiple games with general reward settings and different opponent types. The Multi-Agent Reinforcement Learning in MalmO (MARLO) competition is a new challenge that proposes research in this domain using multiple 3D games. The goal of this contest is to foster research in general agents that can learn across different games and opponent types, proposing a challenge as a milestone in the direction of Artificial General Intelligence." @default.
• W2913103105 created "2019-02-21" @default.
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• W2913103105 date "2019-01-23" @default.
• W2913103105 modified "2023-10-16" @default.
• W2913103105 title "The Multi-Agent Reinforcement Learning in MalmÖ (MARLÖ) Competition" @default.
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