Atari Games On Atari 2600 Freeway

Score

Ergebnisse

Leistungsergebnisse verschiedener Modelle zu diesem Benchmark

		Paper Title
Go-Explore	34	First return, then explore
QR-DQN-1	34	Distributional Reinforcement Learning with Quantile Regression
GDI-I3	34	Generalized Data Distribution Iteration
GDI-H3	34	Generalized Data Distribution Iteration
GDI-H3(200M frames)	34	Generalized Data Distribution Iteration
IQN	34	Implicit Quantile Networks for Distributional Reinforcement Learning
GDI-I3	34	GDI: Rethinking What Makes Reinforcement Learning Different From Supervised Learning
TRPO-hash	34.0	#Exploration: A Study of Count-Based Exploration for Deep Reinforcement Learning
NoisyNet-Dueling	34	Noisy Networks for Exploration
Bootstrapped DQN	33.9	Deep Exploration via Bootstrapped DQN
C51 noop	33.9	A Distributional Perspective on Reinforcement Learning
ASL DDQN	33.9	Train a Real-world Local Path Planner in One Hour via Partially Decoupled Reinforcement Learning and Vectorized Diversity
MuZero (Res2 Adam)	33.87	Online and Offline Reinforcement Learning by Planning with a Learned Model
Ape-X	33.7	Distributed Prioritized Experience Replay
Prior noop	33.7	Prioritized Experience Replay
DDQN+Pop-Art noop	33.4	Learning values across many orders of magnitude
DDQN (tuned) noop	33.3	Dueling Network Architectures for Deep Reinforcement Learning
MuZero	33.03	Mastering Atari, Go, Chess and Shogi by Planning with a Learned Model
DreamerV2	33	Mastering Atari with Discrete World Models
Prior+Duel noop	33.0	Dueling Network Architectures for Deep Reinforcement Learning

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