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1807.01281
Cited By
Human-level performance in first-person multiplayer games with population-based deep reinforcement learning
3 July 2018
Max Jaderberg
Wojciech M. Czarnecki
Iain Dunning
Luke Marris
Guy Lever
Antonio García Castañeda
Charlie Beattie
Neil C. Rabinowitz
Ari S. Morcos
Avraham Ruderman
Nicolas Sonnerat
Tim Green
Louise Deason
Joel Z Leibo
David Silver
Demis Hassabis
Koray Kavukcuoglu
T. Graepel
OffRL
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Papers citing
"Human-level performance in first-person multiplayer games with population-based deep reinforcement learning"
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Title
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Meta-trained agents implement Bayes-optimal agents
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Multi-Agent Collaboration via Reward Attribution Decomposition
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Decoupling Representation Learning from Reinforcement Learning
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Efficient Competitive Self-Play Policy Optimization
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RLCFR: Minimize Counterfactual Regret by Deep Reinforcement Learning
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Deep Model-Based Reinforcement Learning for High-Dimensional Problems, a Survey
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127
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Off-Policy Multi-Agent Decomposed Policy Gradients
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Beining Han
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Dynamic Relational Inference in Multi-Agent Trajectories
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A Cordial Sync: Going Beyond Marginal Policies for Multi-Agent Embodied Tasks
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Responsive Safety in Reinforcement Learning by PID Lagrangian Methods
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Deep Reinforcement Learning and its Neuroscientific Implications
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Scaling Imitation Learning in Minecraft
Artemij Amiranashvili
Nicolai Dorka
Wolfram Burgard
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Perception-Prediction-Reaction Agents for Deep Reinforcement Learning
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Valentin Dalibard
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A Benchmarking Framework for Interactive 3D Applications in the Cloud
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Danny H. K. Tsang
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Sample Factory: Egocentric 3D Control from Pixels at 100000 FPS with Asynchronous Reinforcement Learning
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Zhehui Huang
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Pipeline PSRO: A Scalable Approach for Finding Approximate Nash Equilibria in Large Games
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Shared Experience Actor-Critic for Multi-Agent Reinforcement Learning
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Learning to Play No-Press Diplomacy with Best Response Policy Iteration
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I. Gemp
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Roman Werpachowski
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Yoram Bachrach
106
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08 Jun 2020
A Comparison of Self-Play Algorithms Under a Generalized Framework
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Kevin Denamganai
Sam Devlin
Spyridon Samothrakis
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08 Jun 2020
Causality and Batch Reinforcement Learning: Complementary Approaches To Planning In Unknown Domains
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Manipulating the Distributions of Experience used for Self-Play Learning in Expert Iteration
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72
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Accelerating Deep Neuroevolution on Distributed FPGAs for Reinforcement Learning Problems
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Nicolas Antoine
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29
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Navigating the Landscape of Multiplayer Games
Shayegan Omidshafiei
K. Tuyls
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Paul Muller
Julien Perolat
Bart De Vylder
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Rémi Munos
32
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The AI Economist: Improving Equality and Productivity with AI-Driven Tax Policies
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Sunil Srinivasa
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R. Socher
60
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Real World Games Look Like Spinning Tops
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Gauthier Gidel
Brendan D. Tracey
K. Tuyls
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David Balduzzi
Max Jaderberg
75
101
0
20 Apr 2020
Energy-Based Imitation Learning
Minghuan Liu
Tairan He
Minkai Xu
Weinan Zhang
118
48
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20 Apr 2020
Meta-Learning in Neural Networks: A Survey
Timothy M. Hospedales
Antreas Antoniou
P. Micaelli
Amos Storkey
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420
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11 Apr 2020
CURL: Contrastive Unsupervised Representations for Reinforcement Learning
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Pieter Abbeel
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148
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How Do You Act? An Empirical Study to Understand Behavior of Deep Reinforcement Learning Agents
Richard Meyes
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Tobias Meisen
55
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07 Apr 2020
Obstacle Tower Without Human Demonstrations: How Far a Deep Feed-Forward Network Goes with Reinforcement Learning
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J. Jitsev
Mike Preuss
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49
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Fiber: A Platform for Efficient Development and Distributed Training for Reinforcement Learning and Population-Based Methods
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Rui Wang
Jeff Clune
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Multi-Agent Reinforcement Learning for Problems with Combined Individual and Team Reward
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41
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Human AI interaction loop training: New approach for interactive reinforcement learning
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6
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FormulaZero: Distributionally Robust Online Adaptation via Offline Population Synthesis
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Matthew O'Kelly
Hongrui Zheng
Rahul Mangharam
John C. Duchi
Russ Tedrake
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RIDE: Rewarding Impact-Driven Exploration for Procedurally-Generated Environments
Roberta Raileanu
Tim Rocktaschel
88
174
0
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