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

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Showing 151–200 of 625 papers

TitleStatusHype
GRIm-RePR: Prioritising Generating Important Features for Pseudo-Rehearsal—0
High Performance Across Two Atari Paddle Games Using the Same Perceptual Control Architecture Without Training—0
Interpreting the Learned Model in MuZero Planning—0
From "What" to "When" -- a Spiking Neural Network Predicting Rare Events and Time to their Occurrence—0
From Code to Play: Benchmarking Program Search for Games Using Large Language Models—0
GDI: Rethinking What Makes Reinforcement Learning Different From Supervised Learning—0
CASA: Bridging the Gap between Policy Improvement and Policy Evaluation with Conflict Averse Policy Iteration—0
Adaptive Q-Network: On-the-fly Target Selection for Deep Reinforcement Learning—0
FRESH: Interactive Reward Shaping in High-Dimensional State Spaces using Human Feedback—0
GDI: Rethinking What Makes Reinforcement Learning Different from Supervised Learning—0
An Entropy Regularization Free Mechanism for Policy-based Reinforcement Learning—0
DQN with model-based exploration: efficient learning on environments with sparse rewards—0
Fast Retinomorphic Event Stream for Video Recognition and Reinforcement Learning—0
Double A3C: Deep Reinforcement Learning on OpenAI Gym Games—0
Adaptive N-step Bootstrapping with Off-policy Data—0
Biased Estimates of Advantages over Path Ensembles—0
A Convergent Variant of the Boltzmann Softmax Operator in Reinforcement Learning—0
Exploration by Uncertainty in Reward Space—0
Beyond Exponentially Discounted Sum: Automatic Learning of Return Function—0
Distributional Reinforcement Learning for Efficient Exploration—0
An Approach to Partial Observability in Games: Learning to Both Act and Observe—0
Expressiveness in Deep Reinforcement Learning—0
Distributional Perturbation for Efficient Exploration in Distributional Reinforcement Learning—0
Analysis of Q-learning with Adaptation and Momentum Restart for Gradient Descent—0
Accelerated Target Updates for Q-learning—0
Exploration by Random Network Distillation—0
Disentangling the Causes of Plasticity Loss in Neural Networks—0
Double Prioritized State Recycled Experience Replay—0
Disentangling Controllable Object through Video Prediction Improves Visual Reinforcement Learning—0
DR3: Value-Based Deep Reinforcement Learning Requires Explicit Regularization—0
DSAC-C: Constrained Maximum Entropy for Robust Discrete Soft-Actor Critic—0
CAN ALTQ LEARN FASTER: EXPERIMENTS AND THEORY—0
Dynamic Frame skip Deep Q Network—0
A new Potential-Based Reward Shaping for Reinforcement Learning Agent—0
Effects of Different Optimization Formulations in Evolutionary Reinforcement Learning on Diverse Behavior Generation—0
Efficient decorrelation of features using Gramian in Reinforcement Learning—0
Cautious Policy Programming: Exploiting KL Regularization in Monotonic Policy Improvement for Reinforcement Learning—0
Efficient Diversity-based Experience Replay for Deep Reinforcement Learning—0
An initial attempt of combining visual selective attention with deep reinforcement learning—0
Efficient Entropy for Policy Gradient with Multidimensional Action Space—0
Benchmarking Bonus-Based Exploration Methods on the Arcade Learning Environment—0
Smaller World Models for Reinforcement Learning—0
Efficiently Guiding Imitation Learning Agents with Human Gaze—0
Analysing Results from AI Benchmarks: Key Indicators and How to Obtain Them—0
A Comparison of learning algorithms on the Arcade Learning Environment—0
Combating Reinforcement Learning's Sisyphean Curse with Intrinsic Fear—0
Emergence of Novelty in Evolutionary Algorithms—0
Emphatic Algorithms for Deep Reinforcement Learning—0
Detecting Adversarial Directions in Deep Reinforcement Learning to Make Robust Decisions—0
An advantage actor-critic algorithm for robotic motion planning in dense and dynamic scenarios—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1GDI-I3(200M frames)Score864—Unverified
2GDI-H3(200M frames)Score864—Unverified
3GDI-H3Score864—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
1IQNScore34—Unverified
2QR-DQN-1Score34—Unverified
3TRPO-hashScore34—Unverified
4NoisyNet-DuelingScore34—Unverified
5GDI-H3Score34—Unverified
6GDI-H3(200M frames)Score34—Unverified
7GDI-I3Score34—Unverified
8Go-ExploreScore34—Unverified
9Bootstrapped DQNScore33.9—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-H3Score1,000,000—Unverified
2GDI-H3(200M frames)Score1,000,000—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