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20162026
most citedMastering Chess and Shogi by Self-Play with a General Reinforcement Learning Algorithm

1.1k citations · 2.9k across the 24 of their papers we have counts for

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Showing 2018Show all

5 papers · 1 filter

cs.LG2018

Human-level performance in first-person multiplayer games with population-based deep reinforcement learning

Max Jaderberg, Wojciech M. Czarnecki, Iain Dunning +15

Recent progress in artificial intelligence through reinforcement learning (RL) has shown great success on increasingly complex single-agent environments and two-player turn-based g…

cs.LG2018

Unsupervised Predictive Memory in a Goal-Directed Agent

Greg Wayne, Chia-Chun Hung, David Amos +21

Animals execute goal-directed behaviours despite the limited range and scope of their sensors. To cope, they explore environments and store memories maintaining estimates of import…

stat.ML2018

Memory-based Parameter Adaptation

Pablo Sprechmann, Siddhant M. Jayakumar, Jack W. Rae +7

Deep neural networks have excelled on a wide range of problems, from vision to language and game playing. Neural networks very gradually incorporate information into weights as the…

cs.LG2018

Learning and Querying Fast Generative Models for Reinforcement Learning

Lars Buesing, Theophane Weber, Sebastien Racaniere +8

A key challenge in model-based reinforcement learning (RL) is to synthesize computationally efficient and accurate environment models. We show that carefully designed generative mo…

cs.AI2018

Psychlab: A Psychology Laboratory for Deep Reinforcement Learning Agents

Joel Z. Leibo, Cyprien de Masson d'Autume, Daniel Zoran +10

Psychlab is a simulated psychology laboratory inside the first-person 3D game world of DeepMind Lab (Beattie et al. 2016). Psychlab enables implementations of classical laboratory…