Adam White

According to our database, Adam White authored at least 57 papers between 2006 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

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

Richard S. Sutton, Marlos C. Machado, G. Zacharias Holland, David Szepesvari, Finbarr Timbers, Brian Tanner, Adam White

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

2023

Reward-respecting subtasks for model-based reinforcement learning.

Richard S. Sutton, Marlos C. Machado, G. Zacharias Holland, David Szepesvari, Finbarr Timbers, Brian Tanner, Adam White

Artif. Intell., November, 2023

From eye-blinks to state construction: Diagnostic benchmarks for online representation learning.

Banafsheh Rafiee, Zaheer Abbas, Sina Ghiassian, Raksha Kumaraswamy, Richard S. Sutton, Elliot A. Ludvig, Adam White

Adapt. Behav., February, 2023

Investigating Action Encodings in Recurrent Neural Networks in Reinforcement Learning.

Matthew Schlegel, Volodymyr Tkachuk, Adam M. White, Martha White

Trans. Mach. Learn. Res., 2023

GVFs in the Real World: Making Predictions Online for Water Treatment.

Muhammad Kamran Janjua, Haseeb Shah, Martha White, Erfan Miahi, Marlos C. Machado, Adam White

CoRR, 2023

Harnessing Discrete Representations For Continual Reinforcement Learning.

Edan Meyer, Adam White, Marlos C. Machado

CoRR, 2023

Recurrent Linear Transformers.

Subhojeet Pramanik, Esraa Elelimy, Marlos C. Machado, Adam White

CoRR, 2023

Empirical Design in Reinforcement Learning.

Andrew Patterson, Samuel Neumann, Martha White, Adam White

CoRR, 2023

The In-Sample Softmax for Offline Reinforcement Learning.

Chenjun Xiao, Han Wang, Yangchen Pan, Adam White, Martha White

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Greedy Actor-Critic: A New Conditional Cross-Entropy Method for Policy Improvement.

Samuel Neumann, Sungsu Lim, Ajin George Joseph, Yangchen Pan, Adam White, Martha White

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Auxiliary task discovery through generate-and-test.

Banafsheh Rafiee, Sina Ghiassian, Jun Jin, Richard S. Sutton, Jun Luo, Adam White

Proceedings of the Conference on Lifelong Learning Agents, 2023

Measuring and Mitigating Interference in Reinforcement Learning.

Vincent Liu, Han Wang, Ruo Yu Tao, Khurram Javed, Adam White, Martha White

Proceedings of the Conference on Lifelong Learning Agents, 2023

Loss of Plasticity in Continual Deep Reinforcement Learning.

Zaheer Abbas, Rosie Zhao, Joseph Modayil, Adam White, Marlos C. Machado

Proceedings of the Conference on Lifelong Learning Agents, 2023

Entropy as a Measure of Puzzle Difficulty.

Eugene You Chen Chen, Adam White, Nathan R. Sturtevant

Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment, 2023

2022

No More Pesky Hyperparameters: Offline Hyperparameter Tuning for RL.

Han Wang, Archit Sakhadeo, Adam M. White, James Bell, Vincent Liu, Xutong Zhao, Puer Liu, Tadashi Kozuno, Alona Fyshe, Martha White

Trans. Mach. Learn. Res., 2022

A Generalized Projected Bellman Error for Off-policy Value Estimation in Reinforcement Learning.

Andrew Patterson, Adam White, Martha White

J. Mach. Learn. Res., 2022

Agent-State Construction with Auxiliary Inputs.

Ruo Yu Tao, Adam White, Marlos C. Machado

CoRR, 2022

Goal-Space Planning with Subgoal Models.

Chunlok Lo, Gabor Mihucz, Adam White, Farzane Aminmansour, Martha White

CoRR, 2022

What makes useful auxiliary tasks in reinforcement learning: investigating the effect of the target policy.

Banafsheh Rafiee, Jun Jin, Jun Luo, Adam White

CoRR, 2022

Investigating the Properties of Neural Network Representations in Reinforcement Learning.

Han Wang, Erfan Miahi, Martha White, Marlos C. Machado, Zaheer Abbas, Raksha Kumaraswamy, Vincent Liu, Adam White

CoRR, 2022

The Frost Hollow Experiments: Pavlovian Signalling as a Path to Coordination and Communication Between Agents.

Patrick M. Pilarski, Andrew Butcher, Elnaz Davoodi, Michael Bradley Johanson, Dylan J. A. Brenneis, Adam S. R. Parker, Leslie Acker, Matthew M. Botvinick, Joseph Modayil, Adam White

CoRR, 2022

Pavlovian Signalling with General Value Functions in Agent-Agent Temporal Decision Making.

Andrew Butcher, Michael Bradley Johanson, Elnaz Davoodi, Dylan J. A. Brenneis, Leslie Acker, Adam S. R. Parker, Adam White, Joseph Modayil, Patrick M. Pilarski

CoRR, 2022

Learning Expected Emphatic Traces for Deep RL.

Ray Jiang, Shangtong Zhang, Veronica Chelu, Adam White, Hado van Hasselt

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021

General Value Function Networks.

Matthew Schlegel, Andrew Jacobsen, Zaheer Abbas, Andrew Patterson, Adam White, Martha White

J. Artif. Intell. Res., 2021

Assessing Human Interaction in Virtual Reality With Continually Learning Prediction Agents Based on Reinforcement Learning Algorithms: A Pilot Study.

Dylan J. A. Brenneis, Adam S. R. Parker, Michael Bradley Johanson, Andrew Butcher, Elnaz Davoodi, Leslie Acker, Matthew M. Botvinick, Joseph Modayil, Adam White, Patrick M. Pilarski

CoRR, 2021

A Generalized Projected Bellman Error for Off-policy Value Estimation in Reinforcement Learning.

Andrew Patterson, Adam White, Sina Ghiassian, Martha White

CoRR, 2021

Continual Auxiliary Task Learning.

Matthew McLeod, Chunlok Lo, Matthew Schlegel, Andrew Jacobsen, Raksha Kumaraswamy, Martha White, Adam White

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Emphatic Algorithms for Deep Reinforcement Learning.

Ray Jiang, Tom Zahavy, Zhongwen Xu, Adam White, Matteo Hessel, Charles Blundell, Hado van Hasselt

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

2020

Adapting Behavior via Intrinsic Reward: A Survey and Empirical Study.

Cam Linke, Nadia M. Ady, Martha White, Thomas Degris, Adam White

J. Artif. Intell. Res., 2020

Towards a practical measure of interference for reinforcement learning.

Vincent Liu, Adam White, Hengshuai Yao, Martha White

CoRR, 2020

Gradient Temporal-Difference Learning with Regularized Corrections.

Sina Ghiassian, Andrew Patterson, Shivam Garg, Dhawal Gupta, Adam White, Martha White

Proceedings of the 37th International Conference on Machine Learning, 2020

Training Recurrent Neural Networks Online by Learning Explicit State Variables.

Somjit Nath, Vincent Liu, Alan Chan, Xin Li, Adam White, Martha White

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

Improving Performance in Reinforcement Learning by Breaking Generalization in Neural Networks.

Sina Ghiassian, Banafsheh Rafiee, Yat Long Lo, Adam White

Proceedings of the 19th International Conference on Autonomous Agents and Multiagent Systems, 2020

2019

Adapting Behaviour via Intrinsic Reward: A Survey and Empirical Study.

Cam Linke, Nadia M. Ady, Martha White, Thomas Degris, Adam White

CoRR, 2019

Planning with Expectation Models.

Yi Wan, Muhammad Zaheer, Adam White, Martha White, Richard S. Sutton

Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

Prediction in Intelligence: An Empirical Comparison of Off-policy Algorithms on Robots.

Banafsheh Rafiee, Sina Ghiassian, Adam White, Richard S. Sutton

Proceedings of the 18th International Conference on Autonomous Agents and MultiAgent Systems, 2019

Meta-Descent for Online, Continual Prediction.

Andrew Jacobsen, Matthew Schlegel, Cameron Linke, Thomas Degris, Adam White, Martha White

Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018

The Barbados 2018 List of Open Issues in Continual Learning.

Tom Schaul, Hado van Hasselt, Joseph Modayil, Martha White, Adam White, Pierre-Luc Bacon, Jean Harb, Shibl Mourad, Marc G. Bellemare, Doina Precup

CoRR, 2018

Online Off-policy Prediction.

Sina Ghiassian, Andrew Patterson, Martha White, Richard S. Sutton, Adam White

CoRR, 2018

General Value Function Networks.

Matthew Schlegel, Adam White, Andrew Patterson, Martha White

CoRR, 2018

Directly Estimating the Variance of the λ-Return Using Temporal-Difference Methods.

Craig Sherstan, Brendan Bennett, Kenny Young, Dylan R. Ashley, Adam White, Martha White, Richard S. Sutton

CoRR, 2018

Comparing Direct and Indirect Temporal-Difference Methods for Estimating the Variance of the Return.

Craig Sherstan, Dylan R. Ashley, Brendan Bennett, Kenny Young, Adam White, Martha White, Richard S. Sutton

Proceedings of the Thirty-Fourth Conference on Uncertainty in Artificial Intelligence, 2018

Context-dependent upper-confidence bounds for directed exploration.

Raksha Kumaraswamy, Matthew Schlegel, Adam White, Martha White

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Organizing Experience: a Deeper Look at Replay Mechanisms for Sample-Based Planning in Continuous State Domains.

Yangchen Pan, Muhammad Zaheer, Adam White, Andrew Patterson, Martha White

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

2017

GQ($λ$) Quick Reference and Implementation Guide.

Adam White, Richard S. Sutton

CoRR, 2017

Accelerated Gradient Temporal Difference Learning.

Yangchen Pan, Adam White, Martha White

Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, 2017

2016

A Greedy Approach to Adapting the Trace Parameter for Temporal Difference Learning.

Martha White, Adam White

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

Investigating Practical Linear Temporal Difference Learning.

Adam White, Martha White

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

Introspective Agents: Confidence Measures for General Value Functions.

Craig Sherstan, Adam White, Marlos C. Machado, Patrick M. Pilarski

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

2014

Multi-timescale nexting in a reinforcement learning robot.

Joseph Modayil, Adam White, Richard S. Sutton

Adapt. Behav., 2014

2012

Acquiring a broad range of empirical knowledge in real time by temporal-difference learning.

Joseph Modayil, Adam White, Patrick M. Pilarski, Richard S. Sutton

Proceedings of the IEEE International Conference on Systems, Man, and Cybernetics, 2012

Scaling life-long off-policy learning.

Adam White, Joseph Modayil, Richard S. Sutton

Proceedings of the 2012 IEEE International Conference on Development and Learning and Epigenetic Robotics, 2012

2011

Horde: a scalable real-time architecture for learning knowledge from unsupervised sensorimotor interaction.

Richard S. Sutton, Joseph Modayil, Michael Delp, Thomas Degris, Patrick M. Pilarski, Adam White, Doina Precup

Proceedings of the 10th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2011), 2011

2010

Report on the 2008 Reinforcement Learning Competition.

Shimon Whiteson, Brian Tanner, Adam White

AI Mag., 2010

Interval Estimation for Reinforcement-Learning Algorithms in Continuous-State Domains.

Martha White, Adam White

Proceedings of the Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010. Proceedings of a meeting held 6-9 December 2010, 2010

2009

RL-Glue: Language-Independent Software for Reinforcement-Learning Experiments.

Brian Tanner, Adam White

J. Mach. Learn. Res., 2009

2006

Feature Construction for Reinforcement Learning in Hearts.

Nathan R. Sturtevant, Adam M. White

Proceedings of the Computers and Games, 5th International Conference, 2006