conftrace_
← Authors

Andre Barreto

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

Achievements

Jump to papers ↓
+15 more ↓ 🧭 Keyword Pioneer 🐣 Hot Topic Early Bird 🌈 Renaissance Researcher (5) 🌉 Interdisciplinary Bridge 🌍 Conference Polyglot (6)
🏃 Academic Marathon (14) 🧭 Keyword Pioneer 🐣 Hot Topic Early Bird 🌟 Keyword Trendsetter Combo (3) 🤝 Dynamic Duo (10) 🏆 Keyword Champion (2) 🔬 Deep Specialist (18) 🧬 Topic Evolution 👑 Triple Crown 🏆 Grand Slam 💎 Century Club (31) 📈 Trend Setter 🔥 Unstoppable (9) ⚡ Prolific Year (6) 🗃️ 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) Rémi 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 ε-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