Atari Games On Atari 2600 Yars Revenge

Metriken

Score

Ergebnisse

Leistungsergebnisse verschiedener Modelle zu diesem Benchmark

		Paper Title
Agent57	998532.37	Agent57: Outperforming the Atari Human Benchmark
R2D2	995048.4	Recurrent Experience Replay in Distributed Reinforcement Learning
GDI-I3	972000	Generalized Data Distribution Iteration
GDI-H3	968090	Generalized Data Distribution Iteration
DNA	564513	DNA: Proximal Policy Optimization with a Dual Network Architecture
MuZero	553311.46	Mastering Atari, Go, Chess and Shogi by Planning with a Learned Model
MuZero (Res2 Adam)	219838.09	Online and Offline Reinforcement Learning by Planning with a Learned Model
DreamerV2	156748	Mastering Atari with Discrete World Models
Ape-X	148594.8	Distributed Prioritized Experience Replay
NoisyNet-Dueling	86101	Noisy Networks for Exploration
IMPALA (deep)	84231.14	IMPALA: Scalable Distributed Deep-RL with Importance Weighted Actor-Learner Architectures
RUDDER	60577	RUDDER: Return Decomposition for Delayed Rewards
ASL DDQN	29231.9	Train a Real-world Local Path Planner in One Hour via Partially Decoupled Reinforcement Learning and Vectorized Diversity
CGP	28838.2	Evolving simple programs for playing Atari games
IQN	28379	Implicit Quantile Networks for Distributional Reinforcement Learning
QR-DQN-1	26447	Distributional Reinforcement Learning with Quantile Regression
Advantage Learning	24240.03	Increasing the Action Gap: New Operators for Reinforcement Learning

0 of 17 row(s) selected.