HyperAIHyperAI

Atari Games On Atari 2600 Atlantis

Metrics

Score

Results

Performance results of various models on this benchmark

Model Name
Score
Paper TitleRepository
IQN978200Implicit Quantile Networks for Distributional Reinforcement Learning-
C51 noop841075.0A Distributional Perspective on Reinforcement Learning-
DDQN (tuned) noop106056.0Dueling Network Architectures for Deep Reinforcement Learning-
Duel noop382572.0Dueling Network Architectures for Deep Reinforcement Learning-
NoisyNet-Dueling972175Noisy Networks for Exploration-
Ape-X944497.5Distributed Prioritized Experience Replay-
Prior noop357324.0Prioritized Experience Replay-
GDI-I33803000Generalized Data Distribution Iteration-
Persistent AL1465250Increasing the Action Gap: New Operators for Reinforcement Learning-
UCT193858The Arcade Learning Environment: An Evaluation Platform for General Agents-
Bootstrapped DQN994500Deep Exploration via Bootstrapped DQN-
ASL DDQN947275Train a Real-world Local Path Planner in One Hour via Partially Decoupled Reinforcement Learning and Vectorized Diversity-
A3C LSTM hs875822.0Asynchronous Methods for Deep Reinforcement Learning-
QR-DQN-1971850Distributional Reinforcement Learning with Quantile Regression-
ES FF (1 hour) noop1267410.0Evolution Strategies as a Scalable Alternative to Reinforcement Learning-
Nature DQN85641.0Human level control through deep reinforcement learning
Advantage Learning553591.67Increasing the Action Gap: New Operators for Reinforcement Learning-
DDQN (tuned) hs319688.0Deep Reinforcement Learning with Double Q-learning-
Agent571528841.76Agent57: Outperforming the Atari Human Benchmark-
POP3D2193605.67Policy Optimization With Penalized Point Probability Distance: An Alternative To Proximal Policy Optimization-
0 of 42 row(s) selected.
Atari Games On Atari 2600 Atlantis | SOTA | HyperAI