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08/17/2023
Diversifying AI: Towards Creative Chess with AlphaZero
In recent years, Artificial Intelligence (AI) systems have surpassed hum...
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02/08/2022
GrASP: Gradient-Based Affordance Selection for Planning
Planning with a learned model is arguably a key component of intelligenc...
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02/12/2021
Discovery of Options via Meta-Learned Subgoals
Temporal abstractions in the form of options have been shown to help rei...
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02/09/2021
Learning State Representations from Random Deep Action-conditional Predictions
In this work, we study auxiliary prediction tasks defined by temporal-di...
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07/09/2020
Learning Retrospective Knowledge with Reverse Reinforcement Learning
We present a Reverse Reinforcement Learning (Reverse RL) approach for re...
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02/28/2020
Self-Tuning Deep Reinforcement Learning
Reinforcement learning (RL) algorithms often require expensive manual or...
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12/15/2019
How Should an Agent Practice?
We present a method for learning intrinsic reward functions to drive the...
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09/10/2019
Discovery of Useful Questions as Auxiliary Tasks
Arguably, intelligent agents ought to be able to discover their own ques...
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03/08/2019
Learning Feature Relevance Through Step Size Adaptation in Temporal-Difference Learning
There is a long history of using meta learning as representation learnin...
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06/22/2018
Many-Goals Reinforcement Learning
All-goals updating exploits the off-policy nature of Q-learning to updat...
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04/10/2018
TIDBD: Adapting Temporal-difference Step-sizes Through Stochastic Meta-descent
In this paper, we introduce a method for adapting the step-sizes of temp...
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12/09/2016
Learning Representations by Stochastic Meta-Gradient Descent in Neural Networks
Representations are fundamental to artificial intelligence. The performa...
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06/09/2016
Face valuing: Training user interfaces with facial expressions and reinforcement learning
An important application of interactive machine learning is extending or...
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04/25/2015
