Atari Games On Atari 2600 Kung Fu Master

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Score

Ergebnisse

Leistungsergebnisse verschiedener Modelle zu diesem Benchmark

Modellname	Score	Paper Title	Repository
Prior noop	39581.0	Prioritized Experience Replay
DQN hs	20882.0	Deep Reinforcement Learning with Double Q-learning
DDQN (tuned) noop	29710.0	Dueling Network Architectures for Deep Reinforcement Learning
A3C LSTM hs	40835.0	Asynchronous Methods for Deep Reinforcement Learning
Advantage Learning	32182.99	Increasing the Action Gap: New Operators for Reinforcement Learning
Prior+Duel noop	48375.0	Dueling Network Architectures for Deep Reinforcement Learning
A3C FF (1 day) hs	3046.0	Asynchronous Methods for Deep Reinforcement Learning
GDI-I3	140440	Generalized Data Distribution Iteration	-
FQF	111138.5	Fully Parameterized Quantile Function for Distributional Reinforcement Learning
DDQN (tuned) hs	30207.0	Deep Reinforcement Learning with Double Q-learning
Bootstrapped DQN	36733.3	Deep Exploration via Bootstrapped DQN
DDQN+Pop-Art noop	34393.0	Learning values across many orders of magnitude	-
CGP	57400	Evolving simple programs for playing Atari games
POP3D	33728	Policy Optimization With Penalized Point Probability Distance: An Alternative To Proximal Policy Optimization
Persistent AL	34650.91	Increasing the Action Gap: New Operators for Reinforcement Learning
GDI-H3 (200M)	1666000	GDI: Rethinking What Makes Reinforcement Learning Different from Supervised Learning	-
DreamerV2	62741	Mastering Atari with Discrete World Models
NoisyNet-Dueling	41672	Noisy Networks for Exploration
Gorila	20620.0	Massively Parallel Methods for Deep Reinforcement Learning
DQN noop	26059.0	Deep Reinforcement Learning with Double Q-learning

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