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05/05/2023
Knowledge Transfer from Teachers to Learners in Growing-Batch Reinforcement Learning
Standard approaches to sequential decision-making exploit an agent's abi...
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04/21/2022
Revisiting Gaussian mixture critics in off-policy reinforcement learning: a sample-based approach
Actor-critic algorithms that make use of distributional policy evaluatio...
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06/15/2021
On Multi-objective Policy Optimization as a Tool for Reinforcement Learning
Many advances that have improved the robustness and efficiency of deep r...
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06/26/2020
Critic Regularized Regression
Offline reinforcement learning (RL), also known as batch RL, offers the ...
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06/01/2020
Acme: A Research Framework for Distributed Reinforcement Learning
Deep reinforcement learning has led to many recent-and groundbreaking-ad...
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09/03/2019
Making Efficient Use of Demonstrations to Solve Hard Exploration Problems
This paper introduces R2D3, an agent that makes efficient use of demonst...
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05/12/2016
Which Learning Algorithms Can Generalize Identity-Based Rules to Novel Inputs?
We propose a novel framework for the analysis of learning algorithms tha...
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08/14/2015
Unbounded Bayesian Optimization via Regularization
Bayesian optimization has recently emerged as a popular and efficient to...
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10/27/2014
Heteroscedastic Treed Bayesian Optimisation
Optimising black-box functions is important in many disciplines, such as...
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03/27/2013