Atari Games On Atari 2600 Montezumas Revenge

Métriques

Score

Résultats

Résultats de performance de divers modèles sur ce benchmark

Nom du modèle	Score	Paper Title	Repository
R2D2	2061.3	Recurrent Experience Replay in Distributed Reinforcement Learning	-
GDI-H3	2500	Generalized Data Distribution Iteration	-
Best Learner	10.7	The Arcade Learning Environment: An Evaluation Platform for General Agents
MP-EB	142	Incentivizing Exploration In Reinforcement Learning With Deep Predictive Models
Sarsa-φ-EB	2745.4	Count-Based Exploration in Feature Space for Reinforcement Learning
DNA	0	DNA: Proximal Policy Optimization with a Dual Network Architecture
DQN+SR	1778.8	Count-Based Exploration with the Successor Representation
A3C FF (1 day) hs	53	Asynchronous Methods for Deep Reinforcement Learning
IMPALA (deep)	0.00	IMPALA: Scalable Distributed Deep-RL with Importance Weighted Actor-Learner Architectures
Prior+Duel hs	24.0	Deep Reinforcement Learning with Double Q-learning
A3C FF hs	67	Asynchronous Methods for Deep Reinforcement Learning
GDI-I3	3000	GDI: Rethinking What Makes Reinforcement Learning Different From Supervised Learning	-
A2C+CoEX	6635	Contingency-Aware Exploration in Reinforcement Learning	-
Advantage Learning	0.42	Increasing the Action Gap: New Operators for Reinforcement Learning
POP3D	0	Policy Optimization With Penalized Point Probability Distance: An Alternative To Proximal Policy Optimization
Nature DQN	0	Human level control through deep reinforcement learning
DDQN-PC	3459	Unifying Count-Based Exploration and Intrinsic Motivation
ASL DDQN	0	Train a Real-world Local Path Planner in One Hour via Partially Decoupled Reinforcement Learning and Vectorized Diversity	-
Gorila	84	Massively Parallel Methods for Deep Reinforcement Learning
Sarsa-ε	399.5	Count-Based Exploration in Feature Space for Reinforcement Learning

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