Marlos C. Machado

Publication Activity (10 Years)

Years Active: 2011-2024
Publications (10 Years): 62

Top Topics

Function Approximation

Eligibility Traces

Reinforcement Learning

Confidence Measures

Top Venues

Publications

Diego Gomez, Michael Bowling, Marlos C. Machado
Proper Laplacian Representation Learning. ICLR (2024)
Han Wang, Erfan Miahi, Martha White, Marlos C. Machado, Zaheer Abbas, Raksha Kumaraswamy, Vincent Liu, Adam White
Investigating the properties of neural network representations in reinforcement learning. Artif. Intell. 330 (2024)
Brett Daley, Marlos C. Machado, Martha White
Demystifying the Recency Heuristic in Temporal-Difference Learning. CoRR (2024)
Muhammad Kamran Janjua, Haseeb Shah, Martha White, Erfan Miahi, Marlos C. Machado, Adam White
GVFs in the real world: making predictions online for water treatment. Mach. Learn. 113 (8) (2024)
Alex Lewandowski, Saurabh Kumar, Dale Schuurmans, András György, Marlos C. Machado
Learning Continually by Spectral Regularization. CoRR (2024)
Richard S. Sutton, Marlos C. Machado, G. Zacharias Holland, David Szepesvari, Finbarr Timbers, Brian Tanner, Adam White
Reward-Respecting Subtasks for Model-Based Reinforcement Learning (Abstract Reprint). AAAI (2024)
Brett Daley, Martha White, Marlos C. Machado
Compound Returns Reduce Variance in Reinforcement Learning. CoRR (2024)
Muhammad Kamran Janjua, Haseeb Shah, Martha White, Erfan Miahi, Marlos C. Machado, Adam White
GVFs in the Real World: Making Predictions Online for Water Treatment. CoRR (2023)
Subhojeet Pramanik, Esraa Elelimy, Marlos C. Machado, Adam White
Recurrent Linear Transformers. CoRR (2023)
Zaheer Abbas, Rosie Zhao, Joseph Modayil, Adam White, Marlos C. Machado
Loss of Plasticity in Continual Deep Reinforcement Learning. CoRR (2023)
Alex Lewandowski, Haruto Tanaka, Dale Schuurmans, Marlos C. Machado
Curvature Explains Loss of Plasticity. CoRR (2023)
Brett Daley, Martha White, Christopher Amato, Marlos C. Machado
Trajectory-Aware Eligibility Traces for Off-Policy Reinforcement Learning. CoRR (2023)
Richard S. Sutton, Marlos C. Machado, G. Zacharias Holland, David Szepesvari, Finbarr Timbers, Brian Tanner, Adam White
Reward-respecting subtasks for model-based reinforcement learning. Artif. Intell. 324 (2023)
Martin Klissarov, Marlos C. Machado
Deep Laplacian-based Options for Temporally-Extended Exploration. ICML (2023)
Marlos C. Machado, André Barreto, Doina Precup, Michael Bowling
Temporal Abstraction in Reinforcement Learning with the Successor Representation. J. Mach. Learn. Res. 24 (2023)
Zaheer Abbas, Rosie Zhao, Joseph Modayil, Adam White, Marlos C. Machado
Loss of Plasticity in Continual Deep Reinforcement Learning. CoLLAs (2023)
Edan Meyer, Adam White, Marlos C. Machado
Harnessing Discrete Representations For Continual Reinforcement Learning. CoRR (2023)
Ruo Yu Tao, Adam White, Marlos C. Machado
Agent-State Construction with Auxiliary Inputs. Trans. Mach. Learn. Res. 2023 (2023)
Diego Gomez, Michael Bowling, Marlos C. Machado
Proper Laplacian Representation Learning. CoRR (2023)
Brett Daley, Martha White, Christopher Amato, Marlos C. Machado
Trajectory-Aware Eligibility Traces for Off-Policy Reinforcement Learning. ICML (2023)
Martin Klissarov, Marlos C. Machado
Deep Laplacian-based Options for Temporally-Extended Exploration. CoRR (2023)
Akram Erraqabi, Marlos C. Machado, Mingde Zhao, Sainbayar Sukhbaatar, Alessandro Lazaric, Ludovic Denoyer, Yoshua Bengio
Temporal Abstractions-Augmented Temporally Contrastive Learning: An Alternative to the Laplacian in RL. CoRR (2022)
Akram Erraqabi, Marlos C. Machado, Mingde Zhao, Sainbayar Sukhbaatar, Alessandro Lazaric, Ludovic Denoyer, Yoshua Bengio
Temporal abstractions-augmented temporally contrastive learning: An alternative to the Laplacian in RL. UAI (2022)
Sharan Vaswani, Olivier Bachem, Simone Totaro, Robert Müller, Shivam Garg, Matthieu Geist, Marlos C. Machado, Pablo Samuel Castro, Nicolas Le Roux
A general class of surrogate functions for stable and efficient reinforcement learning. AISTATS (2022)
Han Wang, Erfan Miahi, Martha White, Marlos C. Machado, Zaheer Abbas, Raksha Kumaraswamy, Vincent Liu, Adam White
Investigating the Properties of Neural Network Representations in Reinforcement Learning. CoRR (2022)
Ruo Yu Tao, Adam White, Marlos C. Machado
Agent-State Construction with Auxiliary Inputs. CoRR (2022)
Richard S. Sutton, Marlos C. Machado, G. Zacharias Holland, David Szepesvari, Finbarr Timbers, Brian Tanner, Adam White
Reward-Respecting Subtasks for Model-Based Reinforcement Learning. CoRR (2022)
Rishabh Agarwal, Marlos C. Machado, Pablo Samuel Castro, Marc G. Bellemare
Contrastive Behavioral Similarity Embeddings for Generalization in Reinforcement Learning. CoRR (2021)
Wesley Chung, Valentin Thomas, Marlos C. Machado, Nicolas Le Roux
Beyond Variance Reduction: Understanding the True Impact of Baselines on Policy Optimization. ICML (2021)
Marlos C. Machado, André Barreto, Doina Precup
Temporal Abstraction in Reinforcement Learning with the Successor Representation. CoRR (2021)
Rishabh Agarwal, Marlos C. Machado, Pablo Samuel Castro, Marc G. Bellemare
Contrastive Behavioral Similarity Embeddings for Generalization in Reinforcement Learning. ICLR (2021)
Sharan Vaswani, Olivier Bachem, Simone Totaro, Robert Mueller, Matthieu Geist, Marlos C. Machado, Pablo Samuel Castro, Nicolas Le Roux
A functional mirror ascent view of policy gradient methods with function approximation. CoRR (2021)
Adrien Ali Taïga, William Fedus, Marlos C. Machado, Aaron C. Courville, Marc G. Bellemare
On Bonus-Based Exploration Methods in the Arcade Learning Environment. CoRR (2021)
Dibya Ghosh, Marlos C. Machado, Nicolas Le Roux
An operator view of policy gradient methods. NeurIPS (2020)
Marlos C. Machado, Marc G. Bellemare, Michael Bowling
Count-Based Exploration with the Successor Representation. AAAI (2020)
Wesley Chung, Valentin Thomas, Marlos C. Machado, Nicolas Le Roux
Beyond variance reduction: Understanding the true impact of baselines on policy optimization. CoRR (2020)
Yuu Jinnai, Jee Won Park, Marlos C. Machado, George Dimitri Konidaris
Exploration in Reinforcement Learning with Deep Covering Options. ICLR (2020)
Adrien Ali Taïga, William Fedus, Marlos C. Machado, Aaron C. Courville, Marc G. Bellemare
On Bonus Based Exploration Methods In The Arcade Learning Environment. ICLR (2020)
Dibya Ghosh, Marlos C. Machado, Nicolas Le Roux
An operator view of policy gradient methods. CoRR (2020)
Marc G. Bellemare, Salvatore Candido, Pablo Samuel Castro, Jun Gong, Marlos C. Machado, Subhodeep Moitra, Sameera S. Ponda, Ziyu Wang
Autonomous navigation of stratospheric balloons using reinforcement learning. Nat. 588 (7836) (2020)
Adrien Ali Taïga, William Fedus, Marlos C. Machado, Aaron C. Courville, Marc G. Bellemare
Benchmarking Bonus-Based Exploration Methods on the Arcade Learning Environment. CoRR (2019)
Marlos C. Machado, Marc G. Bellemare, Michael Bowling
Count-Based Exploration with the Successor Representation. CoRR (2018)
Jesse Farebrother, Marlos C. Machado, Michael Bowling
Generalization and Regularization in DQN. CoRR (2018)
Craig Sherstan, Marlos C. Machado, Patrick M. Pilarski
Accelerating Learning in Constructive Predictive Frameworks with the Successor Representation. CoRR (2018)
Craig Sherstan, Marlos C. Machado, Patrick M. Pilarski
Accelerating Learning in Constructive Predictive Frameworks with the Successor Representation. IROS (2018)
Marlos C. Machado, Clemens Rosenbaum, Xiaoxiao Guo, Miao Liu, Gerald Tesauro, Murray Campbell
Eigenoption Discovery through the Deep Successor Representation. ICLR (Poster) (2018)
Marlos C. Machado, Marc G. Bellemare, Erik Talvitie, Joel Veness, Matthew J. Hausknecht, Michael Bowling
Revisiting the Arcade Learning Environment: Evaluation Protocols and Open Problems for General Agents. J. Artif. Intell. Res. 61 (2018)
Marlos C. Machado, Marc G. Bellemare, Erik Talvitie, Joel Veness, Matthew J. Hausknecht, Michael Bowling
Revisiting the Arcade Learning Environment: Evaluation Protocols and Open Problems for General Agents (Extended Abstract). IJCAI (2018)
Marlos C. Machado, Marc G. Bellemare, Michael H. Bowling
A Laplacian Framework for Option Discovery in Reinforcement Learning. CoRR (2017)
Miao Liu, Marlos C. Machado, Gerald Tesauro, Murray Campbell
The Eigenoption-Critic Framework. CoRR (2017)
Marlos C. Machado, Marc G. Bellemare, Michael H. Bowling
A Laplacian Framework for Option Discovery in Reinforcement Learning. ICML (2017)
Marlos C. Machado, Clemens Rosenbaum, Xiaoxiao Guo, Miao Liu, Gerald Tesauro, Murray Campbell
Eigenoption Discovery through the Deep Successor Representation. CoRR (2017)
Marlos C. Machado, Marc G. Bellemare, Erik Talvitie, Joel Veness, Matthew J. Hausknecht, Michael Bowling
Revisiting the Arcade Learning Environment: Evaluation Protocols and Open Problems for General Agents. CoRR (2017)
Marlos C. Machado, Michael H. Bowling
Learning Purposeful Behaviour in the Absence of Rewards. CoRR (2016)
Harm van Seijen, Ashique Rupam Mahmood, Patrick M. Pilarski, Marlos C. Machado, Richard S. Sutton
True Online Temporal-Difference Learning. J. Mach. Learn. Res. 17 (2016)
Craig Sherstan, Adam White, Marlos C. Machado, Patrick M. Pilarski
Introspective Agents: Confidence Measures for General Value Functions. AGI (2016)
Yitao Liang, Marlos C. Machado, Erik Talvitie, Michael H. Bowling
State of the Art Control of Atari Games Using Shallow Reinforcement Learning. AAMAS (2016)
Craig Sherstan, Adam White, Marlos C. Machado, Patrick M. Pilarski
Introspective Agents: Confidence Measures for General Value Functions. CoRR (2016)
Marlos C. Machado, Sriram Srinivasan, Michael H. Bowling
Domain-Independent Optimistic Initialization for Reinforcement Learning. AAAI Workshop: Learning for General Competency in Video Games (2015)
Stefano V. Albrecht, J. Christopher Beck, David L. Buckeridge, Adi Botea, Cornelia Caragea, Chi-Hung Chi, Theodoros Damoulas, Bistra Dilkina, Eric Eaton, Pooyan Fazli, Sam Ganzfried, Marius Lindauer, Marlos C. Machado, Yuri Malitsky, Gary Marcus, Sebastiaan A. Meijer, Francesca Rossi, Arash Shaban-Nejad, Sylvie Thiébaux, Manuela M. Veloso, Toby Walsh, Can Wang, Jie Zhang, Yu Zheng
Reports from the 2015 AAAI Workshop Program. AI Mag. 36 (2) (2015)
Yitao Liang, Marlos C. Machado, Erik Talvitie, Michael H. Bowling
State of the Art Control of Atari Games Using Shallow Reinforcement Learning. CoRR (2015)
Harm van Seijen, Ashique Rupam Mahmood, Patrick M. Pilarski, Marlos C. Machado, Richard S. Sutton
True Online Temporal-Difference Learning. CoRR (2015)
Marlos C. Machado, Sriram Srinivasan, Michael Bowling
Domain-Independent Optimistic Initialization for Reinforcement Learning. CoRR (2014)
Renato Luiz de Freitas Cunha, Marlos C. Machado, Luiz Chaimowicz
RTSMate: Towards an Advice System for RTS Games. Comput. Entertain. 12 (1) (2014)
Marlos C. Machado
A Methodology for Player Modeling based on Machine Learning. CoRR (2013)
Marlos C. Machado, Gisele L. Pappa, Luiz Chaimowicz
A binary classification approach for automatic preference modeling of virtual agents in Civilization IV. CIG (2012)
Marlos C. Machado, Eduardo P. C. Fantini, Luiz Chaimowicz
Player modeling: Towards a common taxonomy. CGAMES (2011)
Marlos C. Machado, Luiz Chaimowicz
Combining Metaheuristics and CSP Algorithms to Solve Sudoku. SBGames (2011)
Marlos C. Machado, Bruno S. L. Rocha, Luiz Chaimowicz
Agents Behavior and Preferences Characterization in Civilization IV. SBGames (2011)