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08/13/2023
Understanding the robustness difference between stochastic gradient descent and adaptive gradient methods
Stochastic gradient descent (SGD) and adaptive gradient methods, such as...
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07/17/2023
An Alternative to Variance: Gini Deviation for Risk-averse Policy Gradient
Restricting the variance of a policy's return is a popular choice in ris...
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03/16/2023
Conditionally Optimistic Exploration for Cooperative Deep Multi-Agent Reinforcement Learning
Efficient exploration is critical in cooperative deep Multi-Agent Reinfo...
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02/28/2023
The In-Sample Softmax for Offline Reinforcement Learning
Reinforcement learning (RL) agents can leverage batches of previously co...
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11/27/2022
Label Alignment Regularization for Distribution Shift
Recent work reported the label alignment property in a supervised learni...
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05/22/2022
Memory-efficient Reinforcement Learning with Knowledge Consolidation
Artificial neural networks are promising as general function approximato...
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12/22/2021
An Alternate Policy Gradient Estimator for Softmax Policies
Policy gradient (PG) estimators for softmax policies are ineffective wit...
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07/19/2020
Beyond Prioritized Replay: Sampling States in Model-Based RL via Simulated Priorities
Model-based reinforcement learning (MBRL) can significantly improve samp...
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02/16/2020
Maxmin Q-learning: Controlling the Estimation Bias of Q-learning
Q-learning suffers from overestimation bias, because it approximates the...
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02/14/2020
An implicit function learning approach for parametric modal regression
For multi-valued functions—such as when the conditional distribution on ...
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02/14/2020
Frequency-based Search-control in Dyna
Model-based reinforcement learning has been empirically demonstrated as ...
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11/19/2019
Deep Tile Coder: an Efficient Sparse Representation Learning Approach with applications in Reinforcement Learning
Representation learning is critical to the success of modern large-scale...
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06/18/2019
Hill Climbing on Value Estimates for Search-control in Dyna
Dyna is an architecture for model-based reinforcement learning (RL), whe...
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10/22/2018
Actor-Expert: A Framework for using Action-Value Methods in Continuous Action Spaces
Value-based approaches can be difficult to use in continuous action spac...
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06/13/2018
Reinforcement Learning with Function-Valued Action Spaces for Partial Differential Equation Control
Recent work has shown that reinforcement learning (RL) is a promising ap...
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06/12/2018
Organizing Experience: A Deeper Look at Replay Mechanisms for Sample-based Planning in Continuous State Domains
Model-based strategies for control are critical to obtain sample efficie...
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11/28/2016
Accelerated Gradient Temporal Difference Learning
The family of temporal difference (TD) methods span a spectrum from comp...
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11/26/2015
