Statements (59)
| Predicate | Object |
|---|---|
| gptkbp:instance_of |
gptkb:Person
|
| gptkbp:bfsLayer |
6
|
| gptkbp:bfsParent |
gptkb:Matthew_W._Taylor
|
| gptkbp:affiliation |
gptkb:University_of_Alberta
|
| gptkbp:author |
gptkb:Andrew_G._Barto
|
| gptkbp:awards |
gptkb:IEEE_Fellow
ACM Fellow |
| gptkbp:birth_date |
gptkb:1956
|
| gptkbp:birth_place |
gptkb:Native_American_tribe
|
| gptkbp:contribution |
Dynamic Programming
Q-learning Markov Decision Processes Ethics in AI Actor-Critic Methods Exploration Strategies Policy Gradient Methods Temporal Difference Learning Approximate Dynamic Programming Learning from Demonstration Hierarchical Reinforcement Learning Bayesian Reinforcement Learning Function Approximation in RL Game Theory in RL Inverse Reinforcement Learning Multi-Agent Reinforcement Learning Reward Shaping Stochastic Control Temporal Abstraction Transfer Learning in RL Applications of RL in Finance Applications of RL in Robotics Policy Iteration Value Iteration Explainability in AI Applications of RL in Autonomous Systems Applications of RL in Gaming Applications of RL in Healthcare Deep Learning in RL Model-Based Reinforcement Learning Robustness in RL Safety in RL Social Learning in RL |
| gptkbp:education |
gptkb:University_of_Alberta
gptkb:University_of_Massachusetts_Amherst |
| gptkbp:field |
gptkb:Artificial_Intelligence
gptkb:software_framework |
| https://www.w3.org/2000/01/rdf-schema#label |
Dr. Richard Sutton
|
| gptkbp:influenced |
gptkb:Deep_Reinforcement_Learning
|
| gptkbp:influenced_by |
gptkb:Marvin_Minsky
|
| gptkbp:known_for |
gptkb:software_framework
|
| gptkbp:mentor |
gptkb:Richard_S._Sutton
|
| gptkbp:notable_alumni |
gptkb:Michael_Littman
gptkb:Satinder_Singh Doina Precup |
| gptkbp:published_by |
Reinforcement Learning: An Introduction
|
| gptkbp:research_interest |
gptkb:robot
Cognitive Science Neuroscience |
| gptkbp:title |
Learning to Predict by the Methods of Temporal Differences
|