Bruno C. da Silva

According to our database, Bruno C. da Silva authored at least 58 papers between 2004 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Abstract Reward Processes: Leveraging State Abstraction for Consistent Off-Policy Evaluation.

Shreyas Chaudhari, Ameet Deshpande, Bruno Castro da Silva, Philip S. Thomas

CoRR, 2024

RLHF Deciphered: A Critical Analysis of Reinforcement Learning from Human Feedback for LLMs.

Shreyas Chaudhari, Pranjal Aggarwal, Vishvak Murahari, Tanmay Rajpurohit, Ashwin Kalyan, Karthik Narasimhan, Ameet Deshpande, Bruno Castro da Silva

CoRR, 2024

Mitigating the Curse of Horizon in Monte-Carlo Returns.

Alex Ayoub, David Szepesvari, Francesco Zanini, Bryan Chan, Dhawal Gupta, Bruno Castro da Silva, Dale Schuurmans

RLJ, 2024

Position: Benchmarking is Limited in Reinforcement Learning Research.

Scott M. Jordan, Adam White, Bruno Castro da Silva, Martha White, Philip S. Thomas

Proceedings of the Forty-first International Conference on Machine Learning, 2024

From Past to Future: Rethinking Eligibility Traces.

Dhawal Gupta, Scott M. Jordan, Shreyas Chaudhari, Bo Liu, Philip S. Thomas, Bruno Castro da Silva

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

Coagent Networks: Generalized and Scaled.

James E. Kostas, Scott M. Jordan, Yash Chandak, Georgios Theocharous, Dhawal Gupta, Martha White, Bruno Castro da Silva, Philip S. Thomas

CoRR, 2023

Behavior Alignment via Reward Function Optimization.

Dhawal Gupta, Yash Chandak, Scott M. Jordan, Philip S. Thomas, Bruno C. da Silva

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

A Toolkit for Reliable Benchmarking and Research in Multi-Objective Reinforcement Learning.

Florian Felten, Lucas N. Alegre, Ann Nowé, Ana L. C. Bazzan, El-Ghazali Talbi, Grégoire Danoy, Bruno C. da Silva

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Multi-Step Generalized Policy Improvement by Leveraging Approximate Models.

Lucas Nunes Alegre, Ana L. C. Bazzan, Ann Nowé, Bruno C. da Silva

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Seldonian Toolkit: Building Software with Safe and Fair Machine Learning.

Austin Hoag, James E. Kostas, Bruno Castro da Silva, Philip S. Thomas, Yuriy Brun

Proceedings of the 45th IEEE/ACM International Conference on Software Engineering: ICSE 2023 Companion Proceedings, 2023

Sample-Efficient Multi-Objective Learning via Generalized Policy Improvement Prioritization.

Lucas Nunes Alegre, Ana L. C. Bazzan, Diederik M. Roijers, Ann Nowé, Bruno C. da Silva

Proceedings of the 2023 International Conference on Autonomous Agents and Multiagent Systems, 2023

2022

Model-Based Reinforcement Learning with SINDy.

Rushiv Arora, Bruno Castro da Silva, Eliot Moss

CoRR, 2022

Enforcing Delayed-Impact Fairness Guarantees.

Aline Weber, Blossom Metevier, Yuriy Brun, Philip S. Thomas, Bruno Castro da Silva

CoRR, 2022

Off-Policy Evaluation for Action-Dependent Non-stationary Environments.

Yash Chandak, Shiv Shankar, Nathaniel D. Bastian, Bruno C. da Silva, Emma Brunskill, Philip S. Thomas

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

Look-Ahead Reinforcement Learning for Load Balancing Network Traffic.

Isadora P. Possebon, Bruno Castro da Silva, Alberto E. Schaeffer-Filho

Proceedings of the IEEE Symposium on Computers and Communications, 2022

Constrained Offline Policy Optimization.

Nicholas Polosky, Bruno C. da Silva, Madalina Fiterau, Jithin Jagannath

Proceedings of the International Conference on Machine Learning, 2022

Optimistic Linear Support and Successor Features as a Basis for Optimal Policy Transfer.

Lucas Nunes Alegre, Ana L. C. Bazzan, Bruno C. da Silva

Proceedings of the International Conference on Machine Learning, 2022

Fairness Guarantees under Demographic Shift.

Stephen Giguere, Blossom Metevier, Bruno Castro da Silva, Yuriy Brun, Philip S. Thomas, Scott Niekum

Proceedings of the Tenth International Conference on Learning Representations, 2022

RADAR: Reactive and Deliberative Adaptive Reasoning - Learning When to Think Fast and When to Think Slow.

Ørjan Strand, Didrik Spanne Reilstad, Zhenying Wu, Bruno Castro da Silva, Jim Torresen, Kai Olav Ellefsen

Proceedings of the IEEE International Conference on Development and Learning, 2022

2021

Quantifying the impact of non-stationarity in reinforcement learning-based traffic signal control.

Lucas Nunes Alegre, Ana L. C. Bazzan, Bruno C. da Silva

PeerJ Comput. Sci., 2021

Patterns of high-risk drinking among medical students: A web-based survey with machine learning.

Grasiela Marcon, Flávia de Ávila Pereira, Aline Zimerman, Bruno Castro da Silva, Lisia von Diemen, Ives Cavalcante Passos, Mariana Recamonde Mendoza

Comput. Biol. Medicine, 2021

Universal Off-Policy Evaluation.

Yash Chandak, Scott Niekum, Bruno C. da Silva, Erik G. Learned-Miller, Emma Brunskill, Philip S. Thomas

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

Posterior Value Functions: Hindsight Baselines for Policy Gradient Methods.

Chris Nota, Philip S. Thomas, Bruno C. da Silva

Proceedings of the 38th International Conference on Machine Learning, 2021

Minimum-Delay Adaptation in Non-Stationary Reinforcement Learning via Online High-Confidence Change-Point Detection.

Lucas Nunes Alegre, Ana L. C. Bazzan, Bruno C. da Silva

Proceedings of the AAMAS '21: 20th International Conference on Autonomous Agents and Multiagent Systems, 2021

2020

Toll-based reinforcement learning for efficient equilibria in route choice.

Gabriel de Oliveira Ramos, Bruno C. da Silva, Roxana Radulescu, Ana L. C. Bazzan, Ann Nowé

Knowl. Eng. Rev., 2020

Data clustering for efficient approximate computing.

Michael Guilherme Jordan, Marcelo Brandalero, Guilherme Meneguzzi Malfatti, Geraldo F. Oliveira, Arthur Francisco Lorenzon, Bruno C. da Silva, Luigi Carro, Mateus B. Rutzig, Antonio Carlos Schneider Beck

Des. Autom. Embed. Syst., 2020

Autonomous learning of multiple, context-dependent tasks.

Vieri Giuliano Santucci, Davide Montella, Bruno Castro da Silva, Gianluca Baldassarre

CoRR, 2020

Optimal Options for Multi-Task Reinforcement Learning Under Time Constraints.

Manuel Del Verme, Bruno Castro da Silva, Gianluca Baldassarre

CoRR, 2020

2019

Autonomous Open-Ended Learning of Interdependent Tasks.

Vieri Giuliano Santucci, Emilio Cartoni, Bruno Castro da Silva, Gianluca Baldassarre

CoRR, 2019

Parameterized Melody Generation with Autoencoders and Temporally-Consistent Noise.

Aline Weber, Lucas Nunes Alegre, Jim Tørresen, Bruno C. da Silva

Proceedings of the 19th International Conference on New Interfaces for Musical Expression, 2019

A Methodology for Neural Network Architectural Tuning Using Activation Occurrence Maps.

Rafael Garcia, Alexandre Xavier Falcão, Alexandru C. Telea, Bruno Castro da Silva, Jim Tørresen, João Luiz Dihl Comba

Proceedings of the International Joint Conference on Neural Networks, 2019

Identifying Reusable Early-Life Options.

Aline Weber, Charles P. Martin, Jim Tørresen, Bruno C. da Silva

Proceedings of the Joint IEEE 9th International Conference on Development and Learning and Epigenetic Robotics, 2019

A Compression-Inspired Framework for Macro Discovery.

Francisco M. Garcia, Bruno C. da Silva, Philip S. Thomas

Proceedings of the 18th International Conference on Autonomous Agents and MultiAgent Systems, 2019

2018

A task-and-technique centered survey on visual analytics for deep learning model engineering.

Rafael Garcia, Alexandru C. Telea, Bruno Castro da Silva, Jim Tørresen, João Luiz Dihl Comba

Comput. Graph., 2018

Efficient Local Memory Support for Approximate Computing.

Marcelo Brandalero, Guilherme Meneguzzi Malfatti, Geraldo Francisco Oliveira, Leonardo Almeida da Silveira, Larissa Rozales Gonçalves, Bruno Castro da Silva, Luigi Carro, Antonio Carlos Schneider Beck

Proceedings of the VIII Brazilian Symposium on Computing Systems Engineering, 2018

Comparing Multi-Armed Bandit Algorithms and Q-learning for Multiagent Action Selection: a Case Study in Route Choice.

Thiago Bell Felix de Oliveira, Ana L. C. Bazzan, Bruno C. da Silva, Ricardo Grunitzki

Proceedings of the 2018 International Joint Conference on Neural Networks, 2018

Towards Designing Optimal Reward Functions in Multi-Agent Reinforcement Learning Problems.

Ricardo Grunitzki, Bruno Castro da Silva, Ana L. C. Bazzan

Proceedings of the 2018 International Joint Conference on Neural Networks, 2018

2017

Identifying Reusable Macros for Efficient Exploration via Policy Compression.

Francisco M. Garcia, Bruno C. da Silva

CoRR, 2017

On Ensuring that Intelligent Machines Are Well-Behaved.

Philip S. Thomas, Bruno Castro da Silva, Andrew G. Barto, Emma Brunskill

CoRR, 2017

Task-based behavior generalization via manifold clustering.

Rafael Garcia, Bruno Castro da Silva, João Luiz Dihl Comba

Proceedings of the 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2017

Learning to Minimise Regret in Route Choice.

Gabriel de Oliveira Ramos, Bruno Castro da Silva, Ana L. C. Bazzan

Proceedings of the 16th Conference on Autonomous Agents and MultiAgent Systems, 2017

A Flexible Approach for Designing Optimal Reward Functions.

Ricardo Grunitzki, Bruno Castro da Silva, Ana L. C. Bazzan

Proceedings of the 16th Conference on Autonomous Agents and MultiAgent Systems, 2017

Context-Based Concurrent Experience Sharing in Multiagent Systems.

Daniel Garant, Bruno Castro da Silva, Victor R. Lesser, Chongjie Zhang

Proceedings of the 16th Conference on Autonomous Agents and MultiAgent Systems, 2017

2016

Using Topological Statistics to Bias and Accelerate Route Choice: Preliminary Findings in Synthetic and Real-World Road Networks.

Fernando Stefanello, Bruno Castro da Silva, Ana L. C. Bazzan

Proceedings of the Ninth International Workshop on Agents in Traffic and Transportation (ATT 2016) co-located with the 25th International Joint Conference On Artificial Intelligence (IJCAI 2016), 2016

Energetic Natural Gradient Descent.

Philip S. Thomas, Bruno Castro da Silva, Christoph Dann, Emma Brunskill

Proceedings of the 33nd International Conference on Machine Learning, 2016

2014

Learning parameterized motor skills on a humanoid robot.

Bruno Castro da Silva, Gianluca Baldassarre, George Dimitri Konidaris, Andrew G. Barto

Proceedings of the 2014 IEEE International Conference on Robotics and Automation, 2014

Active Learning of Parameterized Skills.

Bruno Castro da Silva, George Dimitri Konidaris, Andrew G. Barto

Proceedings of the 31th International Conference on Machine Learning, 2014

2013

Biasing the behavior of organizationally adept agents: (extended abstract).

Daniel D. Corkill, Chongjie Zhang, Bruno Castro da Silva, Yoonheui Kim, Daniel Garant, Victor R. Lesser, Xiaoqin Zhang

Proceedings of the International conference on Autonomous Agents and Multi-Agent Systems, 2013

2012

Learning Parameterized Skills.

Bruno Castro da Silva, George Dimitri Konidaris, Andrew G. Barto

Proceedings of the 29th International Conference on Machine Learning, 2012

TD-DeltaPi: A Model-Free Algorithm for Efficient Exploration.

Bruno Castro da Silva, Andrew G. Barto

Proceedings of the Twenty-Sixth AAAI Conference on Artificial Intelligence, 2012

2010

Learning in groups of traffic signals.

Ana L. C. Bazzan, Denise de Oliveira, Bruno Castro da Silva

Eng. Appl. Artif. Intell., 2010

2007

Distributed constraint propagation for diagnosis of faults in physical processes.

Ana L. C. Bazzan, Bruno Castro da Silva

Proceedings of the 6th International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS 2007), 2007

2006

Dealing with non-stationary environments using context detection.

Bruno Castro da Silva, Eduardo W. Basso, Ana L. C. Bazzan, Paulo Martins Engel

Proceedings of the Machine Learning, 2006

Reinforcement Learning based Control of Traffic Lights in Non-stationary Environments: A Case Study in a Microscopic Simulator.

Denise de Oliveira, Ana L. C. Bazzan, Bruno Castro da Silva, Eduardo W. Basso, Luís Nunes

Proceedings of the 4th European Workshop on Multi-Agent Systems EUMAS'06, 2006

ITSUMO: an Intelligent Transportation System for Urban Mobility.

Bruno Castro da Silva, Robert Junges, Denise de Oliveira, Ana L. C. Bazzan

Proceedings of the 5th International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS 2006), 2006

Improving reinforcement learning with context detection.

Bruno Castro da Silva, Eduardo W. Basso, Filipo Studzinski Perotto, Ana L. C. Bazzan, Paulo Martins Engel

Proceedings of the 5th International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS 2006), 2006

RL-CD: Dealing with Non-Stationarity in Reinforcement Learning.

Bruno Castro da Silva, Eduardo W. Basso, Ana L. C. Bazzan, Paulo Martins Engel

Proceedings of the Proceedings, 2006

2004

ITSUMO: An Intelligent Transportation System for Urban Mobility.

Bruno Castro da Silva, Ana L. C. Bazzan, Gustavo Kuhn Andriotti, Filipe Lopes, Denise de Oliveira

Proceedings of the Innovative Internet Community Systems, 4th InternationalWorkshop, 2004