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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 101–150 of 625 papers

TitleStatusHype
Prioritized Experience ReplayCode1
Deep Reinforcement Learning with Double Q-learningCode1
Deep Recurrent Q-Learning for Partially Observable MDPsCode1
Trust Region Policy OptimizationCode1
Playing Atari with Deep Reinforcement LearningCode1
Generalized Adaptive Transfer Network: Enhancing Transfer Learning in Reinforcement Learning Across DomainsCode0
A Principled Path to Fitted Distributional Evaluation—0
Adaptive Action Duration with Contextual Bandits for Deep Reinforcement Learning in Dynamic EnvironmentsCode0
Meta-learning how to Share Credit among Macro-ActionsCode0
TextAtari: 100K Frames Game Playing with Language AgentsCode0
Improving Performance of Spike-based Deep Q-Learning using Ternary Neurons—0
Automatic Reward Shaping from Confounded Offline Data—0
Frog Soup: Zero-Shot, In-Context, and Sample-Efficient Frogger AgentsCode0
Unraveling the Rainbow: can value-based methods schedule?Code0
SwitchMT: An Adaptive Context Switching Methodology for Scalable Multi-Task Learning in Intelligent Autonomous Agents—0
Pay Attention to What and Where? Interpretable Feature Extractor in Vision-based Deep Reinforcement LearningCode0
Look Before Leap: Look-Ahead Planning with Uncertainty in Reinforcement Learning—0
Adventurer: Exploration with BiGAN for Deep Reinforcement Learning—0
APF+: Boosting adaptive-potential function reinforcement learning methods with a W-shaped network for high-dimensional games—0
Target Return Optimizer for Multi-Game Decision Transformer—0
Learning To Explore With Predictive World Model Via Self-Supervised Learning—0
Reinforcement Learning in Strategy-Based and Atari Games: A Review of Google DeepMinds Innovations—0
Activation by Interval-wise Dropout: A Simple Way to Prevent Neural Networks from Plasticity Loss—0
Objects matter: object-centric world models improve reinforcement learning in visually complex environments—0
Utilizing Evolution Strategies to Train Transformers in Reinforcement LearningCode0
Group-Agent Reinforcement Learning with Heterogeneous Agents—0
A quantum-classical reinforcement learning model to play Atari gamesCode0
MTSpark: Enabling Multi-Task Learning with Spiking Neural Networks for Generalist Agents—0
From Code to Play: Benchmarking Program Search for Games Using Large Language Models—0
Decision Transformer vs. Decision Mamba: Analysing the Complexity of Sequential Decision Making in Atari GamesCode0
Why the Agent Made that Decision: Explaining Deep Reinforcement Learning with Vision Masks—0
Interpreting the Learned Model in MuZero Planning—0
Prosody as a Teaching Signal for Agent Learning: Exploratory Studies and Algorithmic ImplicationsCode0
Efficient Diversity-based Experience Replay for Deep Reinforcement Learning—0
Enhancing Two-Player Performance Through Single-Player Knowledge Transfer: An Empirical Study on Atari 2600 GamesCode0
Interpretable end-to-end Neurosymbolic Reinforcement Learning agents—0
Transforming Game Play: A Comparative Study of DCQN and DTQN Architectures in Reinforcement Learning—0
Reinforcement Learning From Imperfect Corrective Actions And Proxy Rewards—0
Atari-GPT: Benchmarking Multimodal Large Language Models as Low-Level Policies in Atari Games—0
Perceptual Similarity for Measuring Decision-Making Style and Policy Diversity in GamesCode0
Towards Generalizable Reinforcement Learning via Causality-Guided Self-Adaptive Representations—0
PG-Rainbow: Using Distributional Reinforcement Learning in Policy Gradient Methods—0
Normalization and effective learning rates in reinforcement learning—0
Understanding and Diagnosing Deep Reinforcement Learning—0
FDQN: A Flexible Deep Q-Network Framework for Game AutomationCode0
Symmetric Reinforcement Learning Loss for Robust Learning on Diverse Tasks and Model ScalesCode0
Adaptive Q-Network: On-the-fly Target Selection for Deep Reinforcement Learning—0
Learning To Play Atari Games Using Dueling Q-Learning and Hebbian PlasticityCode0
Is Mamba Compatible with Trajectory Optimization in Offline Reinforcement Learning?Code0
Utilizing Maximum Mean Discrepancy Barycenter for Propagating the Uncertainty of Value Functions in Reinforcement Learning—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1GDI-H3(200M frames)Score864—Unverified
2GDI-H3Score864—Unverified
3GDI-I3(200M frames)Score864—Unverified
4GDI-I3Score864—Unverified
5Bootstrapped DQNScore855—Unverified
6FQFScore854.2—Unverified
7R2D2Score837.7—Unverified
8Ape-XScore800.9—Unverified
9Agent57Score790.4—Unverified
10IMPALA (deep)Score787.34—Unverified
#ModelMetricClaimedVerifiedStatus
1GDI-I3Score34—Unverified
2NoisyNet-DuelingScore34—Unverified
3GDI-H3Score34—Unverified
4TRPO-hashScore34—Unverified
5IQNScore34—Unverified
6QR-DQN-1Score34—Unverified
7GDI-H3(200M frames)Score34—Unverified
8Go-ExploreScore34—Unverified
9ASL DDQNScore33.9—Unverified
10C51 noopScore33.9—Unverified
#ModelMetricClaimedVerifiedStatus
1Agent57Score580,328.14—Unverified
2QR-DQN-1Score572,510—Unverified
3R2D2Score408,850—Unverified
4IMPALA (deep)Score351,200.12—Unverified
5Ape-XScore302,391.3—Unverified
6A2C + SILScore104,975.6—Unverified
7MuZero (Res2 Adam)Score94,906.25—Unverified
8DreamerV2Score94,688—Unverified
9MuZeroScore72,276—Unverified
10DNAScore52,398—Unverified
#ModelMetricClaimedVerifiedStatus
1GDI-H3(200M frames)Score1,000,000—Unverified
2GDI-H3Score1,000,000—Unverified
3Agent57Score999,997.63—Unverified
4R2D2Score999,996.7—Unverified
5MuZeroScore999,976.52—Unverified
6MuZero (Res2 Adam)Score999,659.18—Unverified
7GDI-I3Score943,910—Unverified
8Ape-XScore392,952.3—Unverified
9C51 noopScore266,434—Unverified
10Duel noopScore50,254.2—Unverified