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 1–10 of 625 papers

TitleStatusHype
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
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1GDI-H3(200M frames)Score154,380—Unverified
2GDI-H3Score154,380—Unverified
3GDI-I3Score140,460—Unverified
4MuZeroScore74,335.3—Unverified
5Ape-XScore54,681—Unverified
6Agent57Score48,680.86—Unverified
7FQFScore46,498.3—Unverified
8IMPALA (deep)Score43,595.78—Unverified
9R2D2Score43,223.4—Unverified
10IQNScore28,888—Unverified