
Vector Quantized Models for Planning
Recent developments in the field of modelbased RL have proven successfu...
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Learning and Planning in Complex Action Spaces
Many important realworld problems have action spaces that are highdime...
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Online and Offline Reinforcement Learning by Planning with a Learned Model
Learning efficiently from small amounts of data has long been the focus ...
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Machine Translation Decoding beyond Beam Search
Beam search is the goto method for decoding autoregressive machine tra...
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MonteCarlo Tree Search as Regularized Policy Optimization
The combination of MonteCarlo tree search (MCTS) with deep reinforcemen...
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Causally Correct Partial Models for Reinforcement Learning
In reinforcement learning, we can learn a model of future observations a...
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Mastering Atari, Go, Chess and Shogi by Planning with a Learned Model
Constructing agents with planning capabilities has long been one of the ...
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Bayesian Optimization in AlphaGo
During the development of AlphaGo, its many hyperparameters were tuned ...
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Learning to Search with MCTSnets
Planning problems are among the most important and wellstudied problems...
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Mastering Chess and Shogi by SelfPlay with a General Reinforcement Learning Algorithm
The game of chess is the most widelystudied domain in the history of ar...
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Fast NonParametric Tests of Relative Dependency and Similarity
We introduce two novel nonparametric statistical hypothesis tests. The ...
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A Test of Relative Similarity For Model Selection in Generative Models
Probabilistic generative models provide a powerful framework for represe...
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Playing Atari with Deep Reinforcement Learning
We present the first deep learning model to successfully learn control p...
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Ioannis Antonoglou
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