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 226–250 of 625 papers

TitleStatusHype
Exploration by Uncertainty in Reward Space—0
Detecting Adversarial Directions in Deep Reinforcement Learning to Make Robust Decisions—0
Exploratory Not Explanatory: Counterfactual Analysis of Saliency Maps for Deep Reinforcement Learning—0
Control in Stochastic Environment with Delays: A Model-based Reinforcement Learning Approach—0
Learning to play slot cars and Atari 2600 games in just minutes—0
An advantage actor-critic algorithm for robotic motion planning in dense and dynamic scenarios—0
Machine versus Human Attention in Deep Reinforcement Learning Tasks—0
Convex Regularization in Monte-Carlo Tree Search—0
Faster Reinforcement Learning with Value Target Lower Bounding—0
Fast Retinomorphic Event Stream for Video Recognition and Reinforcement Learning—0
A Review for Deep Reinforcement Learning in Atari:Benchmarks, Challenges, and Solutions—0
Improving the Diversity of Bootstrapped DQN by Replacing Priors With Noise—0
Leveraging the Variance of Return Sequences for Exploration Policy—0
Bayesian Q-learning With Imperfect Expert Demonstrations—0
Adversary Agnostic Robust Deep Reinforcement Learning—0
A Benchmark for Low-Switching-Cost Reinforcement Learning—0
From Code to Play: Benchmarking Program Search for Games Using Large Language Models—0
From "What" to "When" -- a Spiking Neural Network Predicting Rare Events and Time to their Occurrence—0
CrowdPlay: Crowdsourcing human demonstration data for offline learning in Atari games—0
GDI: Rethinking What Makes Reinforcement Learning Different From Supervised Learning—0
GDI: Rethinking What Makes Reinforcement Learning Different from Supervised Learning—0
Bayesian Distributional Policy Gradients—0
Deep Reinforcement Learning with Spiking Q-learning—0
A Mathematical Theory of Deep Convolutional Neural Networks for Feature Extraction—0
Deep Reinforcement Learning with Quantum-inspired Experience Replay—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