Atari Games On Atari 2600 Boxing

Score

Results

Performance results of various models on this benchmark

Model Name	Score	Paper Title	Repository
A3C LSTM hs	37.3	Asynchronous Methods for Deep Reinforcement Learning
SARSA	9.8	-	-
MuZero (Res2 Adam)	100	Online and Offline Reinforcement Learning by Planning with a Learned Model
GDI-H3	100	GDI: Rethinking What Makes Reinforcement Learning Different From Supervised Learning	-
Reactor 500M	99.4	The Reactor: A fast and sample-efficient Actor-Critic agent for Reinforcement Learning	-
A3C FF hs	59.8	Asynchronous Methods for Deep Reinforcement Learning
UCT	100	The Arcade Learning Environment: An Evaluation Platform for General Agents
ASL DDQN	99.6	Train a Real-world Local Path Planner in One Hour via Partially Decoupled Reinforcement Learning and Vectorized Diversity	-
A2C + SIL	99.6	Self-Imitation Learning
Agent57	100	Agent57: Outperforming the Atari Human Benchmark
DDQN (tuned) noop	91.6	Dueling Network Architectures for Deep Reinforcement Learning
GDI-H3	100	Generalized Data Distribution Iteration	-
CURL	4.8	CURL: Contrastive Unsupervised Representations for Reinforcement Learning
DNA	99.9	DNA: Proximal Policy Optimization with a Dual Network Architecture
Best Learner	44	The Arcade Learning Environment: An Evaluation Platform for General Agents
Ape-X	100	Distributed Prioritized Experience Replay
DreamerV2	92	Mastering Atari with Discrete World Models
Duel noop	99.4	Dueling Network Architectures for Deep Reinforcement Learning
DQN hs	70.3	Deep Reinforcement Learning with Double Q-learning
IQN	99.8	Implicit Quantile Networks for Distributional Reinforcement Learning

0 of 45 row(s) selected.