Bruno Castro da Silva

Publication Activity (10 Years)

Years Active: 2004-2024
Publications (10 Years): 29

Top Topics

Visual Analytics

Reinforcement Learning

Eligibility Traces

Top Venues

Publications

Scott M. Jordan, Adam White, Bruno Castro da Silva, Martha White, Philip S. Thomas
Position: Benchmarking is Limited in Reinforcement Learning Research. CoRR (2024)
Dhawal Gupta, Scott M. Jordan, Shreyas Chaudhari, Bo Liu, Philip S. Thomas, Bruno Castro da Silva
From Past to Future: Rethinking Eligibility Traces. AAAI (2024)
Shreyas Chaudhari, Pranjal Aggarwal, Vishvak Murahari, Tanmay Rajpurohit, Ashwin Kalyan, Karthik Narasimhan, Ameet Deshpande, Bruno Castro da Silva
RLHF Deciphered: A Critical Analysis of Reinforcement Learning from Human Feedback for LLMs. CoRR (2024)
James E. Kostas, Scott M. Jordan, Yash Chandak, Georgios Theocharous, Dhawal Gupta, Martha White, Bruno Castro da Silva, Philip S. Thomas
Coagent Networks: Generalized and Scaled. CoRR (2023)
Yash Chandak, Shiv Shankar, Nathaniel D. Bastian, Bruno Castro da Silva, Emma Brunskill, Philip S. Thomas
Off-Policy Evaluation for Action-Dependent Non-Stationary Environments. CoRR (2023)
Austin Hoag, James E. Kostas, Bruno Castro da Silva, Philip S. Thomas, Yuriy Brun
Seldonian Toolkit: Building Software with Safe and Fair Machine Learning. ICSE Companion (2023)
Dhawal Gupta, Scott M. Jordan, Shreyas Chaudhari, Bo Liu, Philip S. Thomas, Bruno Castro da Silva
From Past to Future: Rethinking Eligibility Traces. CoRR (2023)
Dhawal Gupta, Yash Chandak, Scott M. Jordan, Philip S. Thomas, Bruno Castro da Silva
Behavior Alignment via Reward Function Optimization. CoRR (2023)
Ørjan Strand, Didrik Spanne Reilstad, Zhenying Wu, Bruno Castro da Silva, Jim Torresen, Kai Olav Ellefsen
RADAR: Reactive and Deliberative Adaptive Reasoning - Learning When to Think Fast and When to Think Slow. ICDL (2022)
Aline Weber, Blossom Metevier, Yuriy Brun, Philip S. Thomas, Bruno Castro da Silva
Enforcing Delayed-Impact Fairness Guarantees. CoRR (2022)
Rushiv Arora, Bruno Castro da Silva, Eliot Moss
Model-Based Reinforcement Learning with SINDy. CoRR (2022)
Stephen Giguere, Blossom Metevier, Bruno Castro da Silva, Yuriy Brun, Philip S. Thomas, Scott Niekum
Fairness Guarantees under Demographic Shift. ICLR (2022)
Yash Chandak, Scott Niekum, Bruno Castro da Silva, Erik G. Learned-Miller, Emma Brunskill, Philip S. Thomas
Universal Off-Policy Evaluation. CoRR (2021)
Grasiela Marcon, Flávia de Ávila Pereira, Aline Zimerman, Bruno Castro da Silva, Lisia von Diemen, Ives Cavalcante Passos, Mariana Recamonde Mendoza
Patterns of high-risk drinking among medical students: A web-based survey with machine learning. Comput. Biol. Medicine 136 (2021)
Vieri Giuliano Santucci, Davide Montella, Bruno Castro da Silva, Gianluca Baldassarre
Autonomous learning of multiple, context-dependent tasks. CoRR (2020)
Manuel Del Verme, Bruno Castro da Silva, Gianluca Baldassarre
Optimal Options for Multi-Task Reinforcement Learning Under Time Constraints. CoRR (2020)
Vieri Giuliano Santucci, Emilio Cartoni, Bruno Castro da Silva, Gianluca Baldassarre
Autonomous Open-Ended Learning of Interdependent Tasks. CoRR (2019)
Rafael Garcia, Alexandre Xavier Falcão, Alexandru C. Telea, Bruno Castro da Silva, Jim Tørresen, João Luiz Dihl Comba
A Methodology for Neural Network Architectural Tuning Using Activation Occurrence Maps. IJCNN (2019)
Rafael Garcia, Alexandru C. Telea, Bruno Castro da Silva, Jim Tørresen, João Luiz Dihl Comba
A task-and-technique centered survey on visual analytics for deep learning model engineering. Comput. Graph. 77 (2018)
Ricardo Grunitzki, Bruno Castro da Silva, Ana L. C. Bazzan
Towards Designing Optimal Reward Functions in Multi-Agent Reinforcement Learning Problems. IJCNN (2018)
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
Efficient Local Memory Support for Approximate Computing. SBESC (2018)
Daniel Garant, Bruno Castro da Silva, Victor R. Lesser, Chongjie Zhang
Context-Based Concurrent Experience Sharing in Multiagent Systems. AAMAS (2017)
Daniel Garant, Bruno Castro da Silva, Victor R. Lesser, Chongjie Zhang
Context-Based Concurrent Experience Sharing in Multiagent Systems. CoRR (2017)
Gabriel de Oliveira Ramos, Bruno Castro da Silva, Ana L. C. Bazzan
Learning to Minimise Regret in Route Choice. AAMAS (2017)
Ricardo Grunitzki, Bruno Castro da Silva, Ana L. C. Bazzan
A Flexible Approach for Designing Optimal Reward Functions. AAMAS (2017)
Philip S. Thomas, Bruno Castro da Silva, Andrew G. Barto, Emma Brunskill
On Ensuring that Intelligent Machines Are Well-Behaved. CoRR (2017)
Rafael Garcia, Bruno Castro da Silva, João Luiz Dihl Comba
Task-based behavior generalization via manifold clustering. IROS (2017)
Fernando Stefanello, Bruno Castro da Silva, Ana L. C. Bazzan
Using Topological Statistics to Bias and Accelerate Route Choice: Preliminary Findings in Synthetic and Real-World Road Networks. ATT@IJCAI (2016)
Philip S. Thomas, Bruno Castro da Silva, Christoph Dann, Emma Brunskill
Energetic Natural Gradient Descent. ICML (2016)
Bruno Castro da Silva, Gianluca Baldassarre, George Dimitri Konidaris, Andrew G. Barto
Learning parameterized motor skills on a humanoid robot. ICRA (2014)
Bruno Castro da Silva, George Dimitri Konidaris, Andrew G. Barto
Active Learning of Parameterized Skills. ICML (2014)
Daniel D. Corkill, Chongjie Zhang, Bruno Castro da Silva, Yoonheui Kim, Daniel Garant, Victor R. Lesser, Xiaoqin Zhang
Biasing the behavior of organizationally adept agents: (extended abstract). AAMAS (2013)
Bruno Castro da Silva, Andrew G. Barto
TD-DeltaPi: A Model-Free Algorithm for Efficient Exploration. AAAI (2012)
Bruno Castro da Silva, George Dimitri Konidaris, Andrew G. Barto
Learning Parameterized Skills. ICML (2012)
Ana L. C. Bazzan, Denise de Oliveira, Bruno Castro da Silva
Learning in groups of traffic signals. Eng. Appl. Artif. Intell. 23 (4) (2010)
Ana L. C. Bazzan, Bruno Castro da Silva
Distributed constraint propagation for diagnosis of faults in physical processes. AAMAS (2007)
Bruno Castro da Silva, Eduardo W. Basso, Filipo Studzinski Perotto, Ana L. C. Bazzan, Paulo Martins Engel
Improving reinforcement learning with context detection. AAMAS (2006)
Bruno Castro da Silva, Eduardo W. Basso, Ana L. C. Bazzan, Paulo Martins Engel
Dealing with non-stationary environments using context detection. ICML (2006)
Bruno Castro da Silva, Robert Junges, Denise de Oliveira, Ana L. C. Bazzan
ITSUMO: an Intelligent Transportation System for Urban Mobility. AAMAS (2006)
Denise de Oliveira, Ana L. C. Bazzan, Bruno Castro da Silva, Eduardo W. Basso, Luís Nunes
Reinforcement Learning based Control of Traffic Lights in Non-stationary Environments: A Case Study in a Microscopic Simulator. EUMAS (2006)
Bruno Castro da Silva, Eduardo W. Basso, Ana L. C. Bazzan, Paulo Martins Engel
RL-CD: Dealing with Non-Stationarity in Reinforcement Learning. AAAI (2006)
Bruno Castro da Silva, Ana L. C. Bazzan, Gustavo Kuhn Andriotti, Filipe Lopes, Denise de Oliveira
ITSUMO: An Intelligent Transportation System for Urban Mobility. IICS (2004)