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János Kramár

2 accepted papers

2020

Learning to Play No-Press Diplomacy with Best Response Policy Iteration

NeurIPS 2020spotlight

Recent advances in deep reinforcement learning (RL) have led to considerable progress in many 2-player zero-sum games, such as Go, Poker and Starcraft. The purely adversarial nature of such games allows for conceptually simple and principled application of RL methods. However real-world settings are…

2019

Relational Forward Models for Multi-Agent Learning

ICLR 2019poster

The behavioral dynamics of multi-agent systems have a rich and orderly structure, which can be leveraged to understand these systems, and to improve how artificial agents learn to operate in them. Here we introduce Relational Forward Models (RFM) for multi-agent learning, networks that can learn to…

Cited by 95SourcePDFScholar