SOTAVerified

Atari Games

The Atari 2600 Games task (and dataset) involves training an agent to achieve high game scores.

( Image credit: Playing Atari with Deep Reinforcement Learning )

Papers

Showing 601625 of 625 papers

TitleStatusHype
The Past and Present of Imitation Learning: A Citation Chain Study0
The Reactor: A fast and sample-efficient Actor-Critic agent for Reinforcement Learning0
The RL Perceptron: Generalisation Dynamics of Policy Learning in High Dimensions0
The Value-Improvement Path: Towards Better Representations for Reinforcement Learning0
Towards automatic construction of multi-network models for heterogeneous multi-task learning0
Reconstructing Actions To Explain Deep Reinforcement Learning0
Towards Consistent Performance on Atari using Expert Demonstrations0
Towards continual learning in medical imaging0
Towards Control-Centric Representations in Reinforcement Learning from Images0
Towards Generalizable Reinforcement Learning via Causality-Guided Self-Adaptive Representations0
Towards Practical Credit Assignment for Deep Reinforcement Learning0
The Benefits of Being Categorical Distributional: Uncertainty-aware Regularized Exploration in Reinforcement Learning0
Towards Understanding Distributional Reinforcement Learning: Regularization, Optimization, Acceleration and Sinkhorn Algorithm0
Training with Worst-Case Distributional Shift causes Overestimation and Inaccuracies in State-Action Value Functions0
Transferring Deep Reinforcement Learning with Adversarial Objective and Augmentation0
Transforming Game Play: A Comparative Study of DCQN and DTQN Architectures in Reinforcement Learning0
Transparency and Explanation in Deep Reinforcement Learning Neural Networks0
Understanding and Diagnosing Deep Reinforcement Learning0
Understanding plasticity in neural networks0
Understanding Visual Concepts with Continuation Learning0
Unlocking the Power of Representations in Long-term Novelty-based Exploration0
Unsupervised Active Pre-Training for Reinforcement Learning0
Using Generative Adversarial Nets on Atari Games for Feature Extraction in Deep Reinforcement Learning0
Continual Learning Using World Models for Pseudo-Rehearsal0
Utilizing Maximum Mean Discrepancy Barycenter for Propagating the Uncertainty of Value Functions in Reinforcement Learning0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1GDI-H3(200M frames)Score864Unverified
2GDI-H3Score864Unverified
3GDI-I3(200M frames)Score864Unverified
4GDI-I3Score864Unverified
5Bootstrapped DQNScore855Unverified
6FQFScore854.2Unverified
7R2D2Score837.7Unverified
8Ape-XScore800.9Unverified
9Agent57Score790.4Unverified
10IMPALA (deep)Score787.34Unverified
#ModelMetricClaimedVerifiedStatus
1GDI-I3Score34Unverified
2NoisyNet-DuelingScore34Unverified
3GDI-H3Score34Unverified
4TRPO-hashScore34Unverified
5IQNScore34Unverified
6QR-DQN-1Score34Unverified
7GDI-H3(200M frames)Score34Unverified
8Go-ExploreScore34Unverified
9ASL DDQNScore33.9Unverified
10C51 noopScore33.9Unverified
#ModelMetricClaimedVerifiedStatus
1Agent57Score580,328.14Unverified
2QR-DQN-1Score572,510Unverified
3R2D2Score408,850Unverified
4IMPALA (deep)Score351,200.12Unverified
5Ape-XScore302,391.3Unverified
6A2C + SILScore104,975.6Unverified
7MuZero (Res2 Adam)Score94,906.25Unverified
8DreamerV2Score94,688Unverified
9MuZeroScore72,276Unverified
10DNAScore52,398Unverified
#ModelMetricClaimedVerifiedStatus
1GDI-H3(200M frames)Score1,000,000Unverified
2GDI-H3Score1,000,000Unverified
3Agent57Score999,997.63Unverified
4R2D2Score999,996.7Unverified
5MuZeroScore999,976.52Unverified
6MuZero (Res2 Adam)Score999,659.18Unverified
7GDI-I3Score943,910Unverified
8Ape-XScore392,952.3Unverified
9C51 noopScore266,434Unverified
10Duel noopScore50,254.2Unverified