← Authors

Andre Barreto

31 papers · 2011–2025 · 6 conferences · across top CS/AI conferences

Achievements

🌍 Conference Polyglot (6) πŸ—ΊοΈ Taxonomy Completionist (38) 🐝 Cross-Pollinator (13) 🌈 Renaissance Researcher (5) πŸŒ‰ Interdisciplinary Bridge πŸƒ Academic Marathon (14) 🧭 Keyword Pioneer 🐣 Hot Topic Early Bird 🌟 Keyword Trendsetter Combo (3) 🀝 Dynamic Duo (10) πŸ† Keyword Champion (2) πŸ”¬ Deep Specialist (18) 🧬 Topic Evolution πŸ‘‘ Triple Crown πŸ† Grand Slam πŸ’Ž Century Club (31) πŸ“ˆ Trend Setter πŸ”₯ Unstoppable (9) ⚑ Prolific Year (6) πŸ—ƒοΈ Keyword Collector (101)

Conferences

NIPS (15) ICML (7) ICLR (4) AAAI (2) JMLR (2) AISTATS (1)

Top co-authors

David Silver (10) Will Dabney (8) Tom Schaul (7) Diana Borsa (7) Doina Precup (6) RΓ©mi Munos (5) Satinder P. Singh (5) Mark Rowland (4) John Quan (4) Georg Ostrovski (3)

Research topics

Applications (1)

Keywords

reinforcement learning (9) value function (8) deep reinforcement learning (7) model-based reinforcement learning (6) transfer learning (5) policy improvement (5) successor feature (5) value function approximation (4) value equivalence (3) value iteration (3) hierarchical reinforcement learning (2) temporal-difference learning (2) representation learning (2) policy learning (2) bellman operator (2) sequential decision making (1) epistemic uncertainty (1) temporal difference learning (1) function approximation (1) continual learning (1)

Papers

Optimizing Return Distributions with Distributional Dynamic Programming JMLR 2025
Position: Video as the New Language for Real-World Decision Making ICML 2024
A Distributional Analogue to the Successor Representation ICML 2024
Temporal Abstraction in Reinforcement Learning with the Successor Representation JMLR 2023
A Definition of Continual Reinforcement Learning NIPS 2023
Deep Reinforcement Learning with Plasticity Injection NIPS 2023
Model-Value Inconsistency as a Signal for Epistemic Uncertainty ICML 2022
The Phenomenon of Policy Churn NIPS 2022
Approximate Value Equivalence NIPS 2022
Generalised Policy Improvement with Geometric Policy Composition ICML 2022
The Value-Improvement Path: Towards Better Representations for Reinforcement Learning AAAI 2021
Proper Value Equivalence NIPS 2021
Risk-Aware Transfer in Reinforcement Learning using Successor Features NIPS 2021
Expected Eligibility Traces AAAI 2021
Temporally-Extended Ξ΅-Greedy Exploration ICLR 2021
Discovering a set of policies for the worst case reward ICLR 2021
On Efficiency in Hierarchical Reinforcement Learning NIPS 2020
Fast Task Inference with Variational Intrinsic Successor Features ICLR 2020
The Value Equivalence Principle for Model-Based Reinforcement Learning NIPS 2020
Composing Entropic Policies using Divergence Correction ICML 2019
The Option Keyboard: Combining Skills in Reinforcement Learning NIPS 2019
Universal Successor Features Approximators ICLR 2019
Adaptive Temporal-Difference Learning for Policy Evaluation with Per-State Uncertainty Estimates NIPS 2019
Transfer in Deep Reinforcement Learning Using Successor Features and Generalised Policy Improvement ICML 2018
Fast deep reinforcement learning using online adjustments from the past NIPS 2018
Natural Value Approximators: Learning when to Trust Past Estimates NIPS 2017
Value-Aware Loss Function for Model-based Reinforcement Learning AISTATS 2017
Successor Features for Transfer in Reinforcement Learning NIPS 2017
The Predictron: End-To-End Learning and Planning ICML 2017
On-line Reinforcement Learning Using Incremental Kernel-Based Stochastic Factorization NIPS 2012
Reinforcement Learning using Kernel-Based Stochastic Factorization NIPS 2011