André Barreto

Orcid: 0000-0001-6168-6972

Affiliations:
  • Google DeepMind
  • National Laboratory for Scientific Computing (LNCC) (former)
  • Federal University of Rio de Janeiro, Brazil (former)


According to our database1, André Barreto authored at least 71 papers between 2000 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

Online presence:

On csauthors.net:

Bibliography

2024
Video as the New Language for Real-World Decision Making.
CoRR, 2024

Position: Video as the New Language for Real-World Decision Making.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

A Distributional Analogue to the Successor Representation.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023
Temporal Abstraction in Reinforcement Learning with the Successor Representation.
J. Mach. Learn. Res., 2023

On the Convergence of Bounded Agents.
CoRR, 2023

Deep Reinforcement Learning with Plasticity Injection.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

A Definition of Continual Reinforcement Learning.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2022
Efficient information diffusion in time-varying graphs through deep reinforcement learning.
World Wide Web, 2022

The Phenomenon of Policy Churn.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Approximate Value Equivalence.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Generalised Policy Improvement with Geometric Policy Composition.
Proceedings of the International Conference on Machine Learning, 2022

Model-Value Inconsistency as a Signal for Epistemic Uncertainty.
Proceedings of the International Conference on Machine Learning, 2022

2021
Approximating Network Centrality Measures Using Node Embedding and Machine Learning.
IEEE Trans. Netw. Sci. Eng., 2021

Temporal Abstraction in Reinforcement Learning with the Successor Representation.
CoRR, 2021

Discovering Diverse Nearly Optimal Policies withSuccessor Features.
CoRR, 2021

Coverage as a Principle for Discovering Transferable Behavior in Reinforcement Learning.
CoRR, 2021

Proper Value Equivalence.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Risk-Aware Transfer in Reinforcement Learning using Successor Features.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Discovering a set of policies for the worst case reward.
Proceedings of the 9th International Conference on Learning Representations, 2021

Temporally-Extended ε-Greedy Exploration.
Proceedings of the 9th International Conference on Learning Representations, 2021

Expected Eligibility Traces.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

The Value-Improvement Path: Towards Better Representations for Reinforcement Learning.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020
Fast reinforcement learning with generalized policy updates.
Proc. Natl. Acad. Sci. USA, 2020

Temporal Difference Uncertainties as a Signal for Exploration.
CoRR, 2020

On Efficiency in Hierarchical Reinforcement Learning.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

The Value Equivalence Principle for Model-Based Reinforcement Learning.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Fast Task Inference with Variational Intrinsic Successor Features.
Proceedings of the 8th International Conference on Learning Representations, 2020

2019
Graph-Based Skill Acquisition For Reinforcement Learning.
ACM Comput. Surv., 2019

Disentangled Cumulants Help Successor Representations Transfer to New Tasks.
CoRR, 2019

General non-linear Bellman equations.
CoRR, 2019

Adaptive Temporal-Difference Learning for Policy Evaluation with Per-State Uncertainty Estimates.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

The Option Keyboard: Combining Skills in Reinforcement Learning.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Composing Entropic Policies using Divergence Correction.
Proceedings of the 36th International Conference on Machine Learning, 2019

Universal Successor Features Approximators.
Proceedings of the 7th International Conference on Learning Representations, 2019

Laplacian using Abstract State Transition Graphs: A Framework for Skill Acquisition.
Proceedings of the 8th Brazilian Conference on Intelligent Systems, 2019

2018
Entropic Policy Composition with Generalized Policy Improvement and Divergence Correction.
CoRR, 2018

Temporal Difference Learning with Neural Networks - Study of the Leakage Propagation Problem.
CoRR, 2018

Unicorn: Continual Learning with a Universal, Off-policy Agent.
CoRR, 2018

Fast deep reinforcement learning using online adjustments from the past.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Transfer in Deep Reinforcement Learning Using Successor Features and Generalised Policy Improvement.
Proceedings of the 35th International Conference on Machine Learning, 2018

Online TD(A) for discrete-time Markov jump linear systems.
Proceedings of the 57th IEEE Conference on Decision and Control, 2018

Abstract State Transition Graphs for Model-Based Reinforcement Learning.
Proceedings of the 7th Brazilian Conference on Intelligent Systems, 2018

2017
Natural Value Approximators: Learning when to Trust Past Estimates.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Successor Features for Transfer in Reinforcement Learning.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

The Predictron: End-To-End Learning and Planning.
Proceedings of the 34th International Conference on Machine Learning, 2017

Count-based quadratic control of Markov jump linear systems with unknown transition probabilities.
Proceedings of the 56th IEEE Annual Conference on Decision and Control, 2017

Value-Aware Loss Function for Model-based Reinforcement Learning.
Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, 2017

2016
Practical Kernel-Based Reinforcement Learning.
J. Mach. Learn. Res., 2016

Successor Features for Transfer in Reinforcement Learning.
CoRR, 2016

Incremental Stochastic Factorization for Online Reinforcement Learning.
Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 2016

2015
Classification-Based Approximate Policy Iteration.
IEEE Trans. Autom. Control., 2015

Reports of the AAAI 2014 Conference Workshops.
AI Mag., 2015

An Expectation-Maximization Algorithm to Compute a Stochastic Factorization From Data.
Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence, 2015

2014
Policy Iteration Based on Stochastic Factorization.
J. Artif. Intell. Res., 2014

Classification-based Approximate Policy Iteration: Experiments and Extended Discussions.
CoRR, 2014

Tree-Based On-Line Reinforcement Learning.
Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence, 2014

2012
On-line Reinforcement Learning Using Incremental Kernel-Based Stochastic Factorization.
Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012

2011
Computing the Stationary Distribution of a Finite Markov Chain Through Stochastic Factorization.
SIAM J. Matrix Anal. Appl., 2011

Reinforcement Learning using Kernel-Based Stochastic Factorization.
Proceedings of the Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 12-14 December 2011, 2011

A new approach for generating numerical constants in grammatical evolution.
Proceedings of the 13th Annual Genetic and Evolutionary Computation Conference, 2011

Evolving Numerical Constants in Grammatical Evolution with the Ephemeral Constant Method.
Proceedings of the Progress in Artificial Intelligence, 2011

2010
Probabilistic performance profiles for the experimental evaluation of stochastic algorithms.
Proceedings of the Genetic and Evolutionary Computation Conference, 2010

Using performance profiles to analyze the results of the 2006 CEC constrained optimization competition.
Proceedings of the IEEE Congress on Evolutionary Computation, 2010

2009
On the characteristics of sequential decision problems and their impact on evolutionary computation.
Proceedings of the Genetic and Evolutionary Computation Conference, 2009

On the Characteristics of Sequential Decision Problems and Their Impact on Evolutionary Computation and Reinforcement Learning.
Proceedings of the Artifical Evolution, 2009

2008
Restricted gradient-descent algorithm for value-function approximation in reinforcement learning.
Artif. Intell., 2008

2007
A note on the variance of rank-based selection strategies for genetic algorithms and genetic programming.
Genet. Program. Evolvable Mach., 2007

2006
GOLS - Genetic orthogonal least squares algorithm for training RBF networks.
Neurocomputing, 2006

Alternative evolutionary algorithms for evolving programs: evolution strategies and steady state GP.
Proceedings of the Genetic and Evolutionary Computation Conference, 2006

2002
Growing Compact RBF Networks Using a Genetic Algorithm.
Proceedings of the 7th Brazilian Symposium on Neural Networks (SBRN 2002), 2002

2000
Graph Layout Using a Genetic Algorithm.
Proceedings of the 6th Brazilian Symposium on Neural Networks (SBRN 2000), 2000


  Loading...