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

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Showing 1–25 of 61 papers

Title	Date	Tasks	Status	Hype	Score
Rainbow: Combining Improvements in Deep Reinforcement Learning	Oct 6, 2017	Atari GamesDeep Reinforcement Learning	CodeCode Available	3	5
Redeeming Intrinsic Rewards via Constrained Optimization	Nov 14, 2022	Atari GamesMontezuma's Revenge	CodeCode Available	1	5
Cell-Free Latent Go-Explore	Aug 31, 2022	Montezuma's RevengeReinforcement Learning (RL)	CodeCode Available	1	5
Exploration by Random Network Distillation	Oct 30, 2018	Atari GamesDeep Reinforcement Learning	CodeCode Available	1	5
A Study of Global and Episodic Bonuses for Exploration in Contextual MDPs	Jun 5, 2023	Montezuma's Revenge	CodeCode Available	1	5
First return, then explore	Apr 27, 2020	Atari GamesMontezuma's Revenge	CodeCode Available	1	5
Hybrid RL: Using Both Offline and Online Data Can Make RL Efficient	Oct 13, 2022	Montezuma's RevengeQ-Learning	CodeCode Available	1	5
Reinforcement Learning with Latent Flow	Jan 6, 2021	Atari Gamescontinuous-control	CodeCode Available	1	5
Flipping Coins to Estimate Pseudocounts for Exploration in Reinforcement Learning	Jun 5, 2023	Montezuma's Revengereinforcement-learning	CodeCode Available	1	5
Go-Explore: a New Approach for Hard-Exploration Problems	Jan 30, 2019	Atari GamesImitation Learning	CodeCode Available	1	5
Open-Ended Reinforcement Learning with Neural Reward Functions	Feb 16, 2022	Montezuma's Revengereinforcement-learning	CodeCode Available	1	5
NovelD: A Simple yet Effective Exploration Criterion	Dec 1, 2021	Atari GamesDeep Reinforcement Learning	CodeCode Available	1	5
PoE-World: Compositional World Modeling with Products of Programmatic Experts	May 16, 2025	Montezuma's RevengeProgram Synthesis	CodeCode Available	1	5
Playing hard exploration games by watching YouTube	May 29, 2018	Deep Reinforcement LearningMontezuma's Revenge	CodeCode Available	1	5
Playing Atari Games with Deep Reinforcement Learning and Human Checkpoint Replay	Jul 18, 2016	Atari GamesDeep Reinforcement Learning	CodeCode Available	0	5
Scaling All-Goals Updates in Reinforcement Learning Using Convolutional Neural Networks	Oct 6, 2018	AllMontezuma's Revenge	CodeCode Available	0	5
Feature Control as Intrinsic Motivation for Hierarchical Reinforcement Learning	May 18, 2017	Hierarchical Reinforcement LearningMontezuma's Revenge	CodeCode Available	0	5
Exploring Unknown States with Action Balance	Mar 10, 2020	Atari GamesDeep Reinforcement Learning	CodeCode Available	0	5
Count-Based Exploration with Neural Density Models	Mar 3, 2017	Atari GamesMontezuma's Revenge	CodeCode Available	0	5
Beating Atari with Natural Language Guided Reinforcement Learning	Apr 18, 2017	Atari GamesDeep Reinforcement Learning	CodeCode Available	0	5
A Study of Plasticity Loss in On-Policy Deep Reinforcement Learning	May 29, 2024	Continual LearningDeep Reinforcement Learning	CodeCode Available	0	5
Hierarchical Deep Reinforcement Learning: Integrating Temporal Abstraction and Intrinsic Motivation	Apr 20, 2016	Deep Reinforcement LearningMontezuma's Revenge	CodeCode Available	0	5
Empowerment-driven Exploration using Mutual Information Estimation	Oct 11, 2018	Deep Reinforcement LearningMontezuma's Revenge	CodeCode Available	0	5
Fine-tuning Reinforcement Learning Models is Secretly a Forgetting Mitigation Problem	Feb 5, 2024	Montezuma's RevengeNetHack	CodeCode Available	0	5
DeepSynth: Automata Synthesis for Automatic Task Segmentation in Deep Reinforcement Learning	Nov 22, 2019	Deep Reinforcement LearningHierarchical Reinforcement Learning	CodeCode Available	0	5

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