SOTAVerified

Montezuma's Revenge

Montezuma's Revenge is an ATARI 2600 Benchmark game that is known to be difficult to perform on for reinforcement learning algorithms. Solutions typically employ algorithms that incentivise environment exploration in different ways.

For the state-of-the art tables, please consult the parent Atari Games task.

( Image credit: Q-map )

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 21–30 of 61 papers

TitleStatusHype
NovelD: A Simple yet Effective Exploration CriterionCode1
Entropic Desired Dynamics for Intrinsic Control—0
On Bonus-Based Exploration Methods in the Arcade Learning Environment—0
Reinforcement Learning with Latent FlowCode1
Learning Abstract Models for Strategic Exploration and Fast Reward TransferCode0
First return, then exploreCode1
Exploring Unknown States with Action BalanceCode0
Bridging the Gap: Providing Post-Hoc Symbolic Explanations for Sequential Decision-Making Problems with Inscrutable Representations—0
MIME: Mutual Information Minimisation Exploration—0
On Bonus Based Exploration Methods In The Arcade Learning Environment—0
Show:102550
← PrevPage 3 of 7Next →

No leaderboard results yet.