Hado P van Hasselt
16 papers · 2014–2023 · 1 venue · across top CS/AI venues
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Research topics
Reinforcement Learning
(15)
Methods
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Machine Learning
(11)
Artificial Intelligence
(9)
Learning Types Β· Machine Learning
(7)
Core AI
(6)
Learning Paradigms Β· Artificial Intelligence
(5)
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(4)
Learning Paradigms Β· Machine Learning
(4)
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(2)
Deep Learning
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Learning Types Β· Deep Learning
(1)
Optimization & Theory
(1)
Keywords
reinforcement learning
(9)
value function
(6)
credit assignment
(3)
temporal difference learning
(2)
policy gradient
(2)
off-policy learning
(2)
auxiliary task
(2)
online learning
(2)
model-based reinforcement learning
(2)
multi-task learning
(1)
deep learning
(1)
policy learning
(1)
neural network optimization
(1)
continual reinforcement learning
(1)
representation learning
(1)
function approximation
(1)
gradient descent
(1)
continual learning
(1)
importance sampling
(1)
forward model
(1)
Papers
A Definition of Continual Reinforcement Learning
NeurIPS 2023
Optimistic Meta-Gradients
NeurIPS 2023
Discovery of Options via Meta-Learned Subgoals
NeurIPS 2021
Self-Consistent Models and Values
NeurIPS 2021
A Self-Tuning Actor-Critic Algorithm
NeurIPS 2020
Discovering Reinforcement Learning Algorithms
NeurIPS 2020
Forethought and Hindsight in Credit Assignment
NeurIPS 2020
Meta-Gradient Reinforcement Learning with an Objective Discovered Online
NeurIPS 2020
Discovery of Useful Questions as Auxiliary Tasks
NeurIPS 2019
Hindsight Credit Assignment
NeurIPS 2019
When to use parametric models in reinforcement learning?
NeurIPS 2019
Meta-Gradient Reinforcement Learning
NeurIPS 2018
Natural Value Approximators: Learning when to Trust Past Estimates
NeurIPS 2017
Successor Features for Transfer in Reinforcement Learning
NeurIPS 2017
Learning values across many orders of magnitude
NeurIPS 2016
Weighted importance sampling for off-policy learning with linear function approximation
NeurIPS 2014