Marlos C. Machado

CoRR, 2024

Investigating the properties of neural network representations in reinforcement learning.

[BibT_eX]

[DOI]

Artif. Intell., 2024

Harnessing Discrete Representations for Continual Reinforcement Learning.

[BibT_eX]

Edan Meyer

Adam White

Proceedings of the 1st Reinforcement Learning Conference, 2024

Demystifying the Recency Heuristic in Temporal-Difference Learning.

[BibT_eX]

Brett Daley

Martha White

Proceedings of the 1st Reinforcement Learning Conference, 2024

Averaging n-step Returns Reduces Variance in Reinforcement Learning.

[BibT_eX]

[DOI]

Brett Daley

Martha White

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Proper Laplacian Representation Learning.

[BibT_eX]

[DOI]

Diego Gomez

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Reward-Respecting Subtasks for Model-Based Reinforcement Learning (Abstract Reprint).

[BibT_eX]

[DOI]

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

Reward-respecting subtasks for model-based reinforcement learning.

[BibT_eX]

[DOI]

Artif. Intell., November, 2023

Agent-State Construction with Auxiliary Inputs.

[BibT_eX]

[DOI]

Ruo Yu Tao

Adam White

Trans. Mach. Learn. Res., 2023

Temporal Abstraction in Reinforcement Learning with the Successor Representation.

[BibT_eX]

[DOI]

J. Mach. Learn. Res., 2023

Curvature Explains Loss of Plasticity.

[BibT_eX]

[DOI]

CoRR, 2023

Recurrent Linear Transformers.

[BibT_eX]

[DOI]

CoRR, 2023

Deep Laplacian-based Options for Temporally-Extended Exploration.

[BibT_eX]

[DOI]

Martin Klissarov

Proceedings of the International Conference on Machine Learning, 2023

Trajectory-Aware Eligibility Traces for Off-Policy Reinforcement Learning.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2023

Loss of Plasticity in Continual Deep Reinforcement Learning.

[BibT_eX]

[DOI]

Proceedings of the Conference on Lifelong Learning Agents, 2023

2022

Temporal abstractions-augmented temporally contrastive learning: An alternative to the Laplacian in RL.

[BibT_eX]

[DOI]

Proceedings of the Uncertainty in Artificial Intelligence, 2022

A general class of surrogate functions for stable and efficient reinforcement learning.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021

Temporal Abstraction in Reinforcement Learning with the Successor Representation.

[BibT_eX]

[DOI]

André Barreto

Doina Precup

CoRR, 2021

A functional mirror ascent view of policy gradient methods with function approximation.

[BibT_eX]

[DOI]

CoRR, 2021

Beyond Variance Reduction: Understanding the True Impact of Baselines on Policy Optimization.

[BibT_eX]

[DOI]

Proceedings of the 38th International Conference on Machine Learning, 2021

Contrastive Behavioral Similarity Embeddings for Generalization in Reinforcement Learning.

[BibT_eX]

[DOI]

Proceedings of the 9th International Conference on Learning Representations, 2021

2020

Autonomous navigation of stratospheric balloons using reinforcement learning.

[BibT_eX]

[DOI]

Nat., 2020

An operator view of policy gradient methods.

[BibT_eX]

[DOI]

Dibya Ghosh

Nicolas Le Roux

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

On Bonus Based Exploration Methods In The Arcade Learning Environment.

[BibT_eX]

[DOI]

Proceedings of the 8th International Conference on Learning Representations, 2020

Exploration in Reinforcement Learning with Deep Covering Options.

[BibT_eX]

[DOI]

Yuu Jinnai

Jee Won Park

George Dimitri Konidaris

Proceedings of the 8th International Conference on Learning Representations, 2020

Count-Based Exploration with the Successor Representation.

[BibT_eX]

[DOI]

Marc G. Bellemare

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019

Benchmarking Bonus-Based Exploration Methods on the Arcade Learning Environment.

[BibT_eX]

[DOI]

CoRR, 2019

2018

Revisiting the Arcade Learning Environment: Evaluation Protocols and Open Problems for General Agents.

[BibT_eX]

[DOI]

Matthew J. Hausknecht

J. Artif. Intell. Res., 2018

Generalization and Regularization in DQN.

[BibT_eX]

[DOI]

Jesse Farebrother

CoRR, 2018

Accelerating Learning in Constructive Predictive Frameworks with the Successor Representation.

[BibT_eX]

[DOI]

Craig Sherstan

Patrick M. Pilarski

Proceedings of the 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2018

Revisiting the Arcade Learning Environment: Evaluation Protocols and Open Problems for General Agents (Extended Abstract).

[BibT_eX]

[DOI]

Matthew J. Hausknecht

Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018

Eigenoption Discovery through the Deep Successor Representation.

[BibT_eX]

[DOI]

Proceedings of the 6th International Conference on Learning Representations, 2018

2017

The Eigenoption-Critic Framework.

[BibT_eX]

[DOI]

CoRR, 2017

A Laplacian Framework for Option Discovery in Reinforcement Learning.

[BibT_eX]

[DOI]

Marc G. Bellemare

Michael H. Bowling

Proceedings of the 34th International Conference on Machine Learning, 2017

2016

True Online Temporal-Difference Learning.

[BibT_eX]

[DOI]

Harm van Seijen

Ashique Rupam Mahmood

Patrick M. Pilarski

Richard S. Sutton

J. Mach. Learn. Res., 2016

Learning Purposeful Behaviour in the Absence of Rewards.

[BibT_eX]

[DOI]

Michael H. Bowling

CoRR, 2016

State of the Art Control of Atari Games Using Shallow Reinforcement Learning.

[BibT_eX]

[DOI]

Proceedings of the 2016 International Conference on Autonomous Agents & Multiagent Systems, 2016

Introspective Agents: Confidence Measures for General Value Functions.

[BibT_eX]

[DOI]

Proceedings of the Artificial General Intelligence - 9th International Conference, 2016

2015

Reports from the 2015 AAAI Workshop Program.

[BibT_eX]

[DOI]

AI Mag., 2015

Domain-Independent Optimistic Initialization for Reinforcement Learning.

[BibT_eX]

[DOI]

Renato Luiz de Freitas Cunha

Sriram Srinivasan

Michael H. Bowling

Proceedings of the Learning for General Competency in Video Games, 2015

2014

RTSMate: Towards an Advice System for RTS Games.

[BibT_eX]

[DOI]

Comput. Entertain., 2014

2013

A Methodology for Player Modeling based on Machine Learning.

[BibT_eX]

[DOI]

CoRR, 2013

2012

A binary classification approach for automatic preference modeling of virtual agents in Civilization IV.

[BibT_eX]

[DOI]

Gisele L. Pappa

Proceedings of the 2012 IEEE Conference on Computational Intelligence and Games, 2012

2011

Agents Behavior and Preferences Characterization in Civilization IV.

[BibT_eX]

[DOI]

Bruno S. L. Rocha

Proceedings of the 2011 Brazilian Symposium on Games and Digital Entertainment, 2011

Combining Metaheuristics and CSP Algorithms to Solve Sudoku.

[BibT_eX]

[DOI]

Proceedings of the 2011 Brazilian Symposium on Games and Digital Entertainment, 2011

Player modeling: Towards a common taxonomy.

[BibT_eX]

[DOI]

Eduardo P. C. Fantini