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Andr\'e Barreto — most-cited papers & profile · Reinforcement Learning
← authors
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overview
Andr\'e Barreto
18
papers ·
353
citations
Google Scholar ↗
Semantic Scholar ↗
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Most-cited papers
Successor Features for Transfer in Reinforcement Learning
2016 · 184 citations
Transfer in Deep Reinforcement Learning Using Successor Features and Generalised Policy Improvement
2019 · 57 citations
Universal Successor Features Approximators
2018 · 24 citations
Fast deep reinforcement learning using online adjustments from the past
2018 · 18 citations
The Value Equivalence Principle for Model-Based Reinforcement Learning
2020 · 11 citations
Risk-Aware Transfer in Reinforcement Learning using Successor Features
2021 · 9 citations
A Definition of Continual Reinforcement Learning
2023 · 9 citations
Deep Reinforcement Learning with Plasticity Injection
2023 · 2 citations
Generalised Policy Improvement with Geometric Policy Composition
2022 · 1 citations
Using Reward Uncertainty to Induce Diverse Behaviour in Reinforcement Learning
2026
Constructing an Optimal Behavior Basis for the Option Keyboard
2025
The Value-Improvement Path: Towards Better Representations for Reinforcement Learning
2020
Expected Eligibility Traces
2020
Proper Value Equivalence
2021
The Option Keyboard: Combining Skills in Reinforcement Learning
2021
Top co-authors
David Silver
· 6
Hado van Hasselt
· 4
John Quan
· 4
R\'emi Munos
· 4
Tom Schaul
· 4
Will Dabney
· 4
Diana Borsa
· 3
Benjamin Van Roy
· 2
Christopher Grimm
· 2
Daniel Mankowitz
· 2
David Abel
· 2
David Silver
· 2
Topics
Value-Based
Meta-RL
Exploration
Model-Based RL
Game AI
Policy Gradient
Safe RL