A survey and critique of multiagent deep reinforcement learning

Deep reinforcement learning (RL) has achieved outstanding results in recent years. This has led to a dramatic increase in the number of applications and methods. Recent works have explored learning beyond single-agent scenarios and have considered multiagent learning (MAL) scenarios. Initial results...

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Vydané v:	Autonomous agents and multi-agent systems Ročník 33; číslo 6; s. 750 - 797
Hlavní autori:	Hernandez-Leal, Pablo, Kartal, Bilal, Taylor, Matthew E.
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	New York Springer US 01.11.2019 Springer Nature B.V
Predmet:	Artificial Intelligence Computer Science Computer Systems Organization and Communication Networks Domains Machine learning Multiagent systems New Horizons in Multiagent Learning Software Engineering/Programming and Operating Systems User Interfaces and Human Computer Interaction Multiagent learning Deep reinforcement learning Multiagent systems Survey Multiagent reinforcement learning
ISSN:	1387-2532, 1573-7454
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