2024
GVFs in the real world: making predictions online for water treatment.
Mach. Learn., July, 2024
MaestroMotif: Skill Design from Artificial Intelligence Feedback.
CoRR, 2024
Plastic Learning with Deep Fourier Features.
CoRR, 2024
Learning Continually by Spectral Regularization.
CoRR, 2024
Compound Returns Reduce Variance in Reinforcement Learning.
CoRR, 2024
Investigating the properties of neural network representations in reinforcement learning.
Artif. Intell., 2024
Harnessing Discrete Representations for Continual Reinforcement Learning.
RLJ, 2024
Demystifying the Recency Heuristic in Temporal-Difference Learning.
RLJ, 2024
Averaging n-step Returns Reduces Variance in Reinforcement Learning.
Proceedings of the Forty-first International Conference on Machine Learning, 2024
Proper Laplacian Representation Learning.
Proceedings of the Twelfth International Conference on Learning Representations, 2024
Reward-Respecting Subtasks for Model-Based Reinforcement Learning (Abstract Reprint).
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024
2023
Reward-respecting subtasks for model-based reinforcement learning.
Artif. Intell., November, 2023
Agent-State Construction with Auxiliary Inputs.
Trans. Mach. Learn. Res., 2023
Temporal Abstraction in Reinforcement Learning with the Successor Representation.
J. Mach. Learn. Res., 2023
Curvature Explains Loss of Plasticity.
CoRR, 2023
Recurrent Linear Transformers.
CoRR, 2023
Deep Laplacian-based Options for Temporally-Extended Exploration.
Proceedings of the International Conference on Machine Learning, 2023
Trajectory-Aware Eligibility Traces for Off-Policy Reinforcement Learning.
Proceedings of the International Conference on Machine Learning, 2023
Loss of Plasticity in Continual Deep Reinforcement Learning.
Proceedings of the Conference on Lifelong Learning Agents, 2023
2022
Temporal abstractions-augmented temporally contrastive learning: An alternative to the Laplacian in RL.
Proceedings of the Uncertainty in Artificial Intelligence, 2022
A general class of surrogate functions for stable and efficient reinforcement learning.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022
2021
Temporal Abstraction in Reinforcement Learning with the Successor Representation.
CoRR, 2021
A functional mirror ascent view of policy gradient methods with function approximation.
CoRR, 2021
Beyond Variance Reduction: Understanding the True Impact of Baselines on Policy Optimization.
Proceedings of the 38th International Conference on Machine Learning, 2021
Contrastive Behavioral Similarity Embeddings for Generalization in Reinforcement Learning.
Proceedings of the 9th International Conference on Learning Representations, 2021
2020
Autonomous navigation of stratospheric balloons using reinforcement learning.
Nat., 2020
An operator view of policy gradient methods.
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.
Proceedings of the 8th International Conference on Learning Representations, 2020
Exploration in Reinforcement Learning with Deep Covering Options.
Proceedings of the 8th International Conference on Learning Representations, 2020
Count-Based Exploration with the Successor Representation.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020
2019
Benchmarking Bonus-Based Exploration Methods on the Arcade Learning Environment.
CoRR, 2019
2018
Revisiting the Arcade Learning Environment: Evaluation Protocols and Open Problems for General Agents.
J. Artif. Intell. Res., 2018
Generalization and Regularization in DQN.
CoRR, 2018
Accelerating Learning in Constructive Predictive Frameworks with the Successor Representation.
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).
Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018
Eigenoption Discovery through the Deep Successor Representation.
Proceedings of the 6th International Conference on Learning Representations, 2018
2017
The Eigenoption-Critic Framework.
CoRR, 2017
A Laplacian Framework for Option Discovery in Reinforcement Learning.
Proceedings of the 34th International Conference on Machine Learning, 2017
2016
True Online Temporal-Difference Learning.
J. Mach. Learn. Res., 2016
Learning Purposeful Behaviour in the Absence of Rewards.
CoRR, 2016
State of the Art Control of Atari Games Using Shallow Reinforcement Learning.
Proceedings of the 2016 International Conference on Autonomous Agents & Multiagent Systems, 2016
Introspective Agents: Confidence Measures for General Value Functions.
Proceedings of the Artificial General Intelligence - 9th International Conference, 2016
2015
Reports from the 2015 AAAI Workshop Program.
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AI Mag., 2015
Domain-Independent Optimistic Initialization for Reinforcement Learning.
Proceedings of the Learning for General Competency in Video Games, 2015
2014
RTSMate: Towards an Advice System for RTS Games.
Comput. Entertain., 2014
2013
A Methodology for Player Modeling based on Machine Learning.
CoRR, 2013
2012
A binary classification approach for automatic preference modeling of virtual agents in Civilization IV.
Proceedings of the 2012 IEEE Conference on Computational Intelligence and Games, 2012
2011
Agents Behavior and Preferences Characterization in Civilization IV.
Proceedings of the 2011 Brazilian Symposium on Games and Digital Entertainment, 2011
Combining Metaheuristics and CSP Algorithms to Solve Sudoku.
Proceedings of the 2011 Brazilian Symposium on Games and Digital Entertainment, 2011
Player modeling: Towards a common taxonomy.
Proceedings of the 16th International Conference on Computer Games, 2011