Bruno Castro da Silva

52 papers A* 10A 8B 2C 2Journal 25Unranked 5

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Enabling Option Learning in Sparse Rewards with Hindsight Experience Replay. CoRR Gabriel Romio, Mateus Begnini Melchiades, Bruno Castro da Silva, Gabriel de Oliveira Ramos
2026	J	`jnl`	RLHF Deciphered: A Critical Analysis of Reinforcement Learning from Human Feedback for LLMs. ACM Comput. Surv. Shreyas Chaudhari, Pranjal Aggarwal, Vishvak Murahari, Tanmay Rajpurohit, Ashwin Kalyan, Karthik Narasimhan, Ameet Deshpande, Bruno Castro da Silva
2025	J	`jnl`	Addressing the Plasticity-Stability Dilemma in Reinforcement Learning. CoRR Mansi Maheshwari, John C. Raisbeck, Bruno Castro da Silva
2025	J	`jnl`	PROMPTMINER: Black-Box Prompt Stealing against Text-to-Image Generative Models via Reinforcement Learning and Fuzz Optimization. CoRR Mingzhe Li, Renhao Zhang, Zhiyang Wen, Siqi Pan, Bruno Castro da Silva, Juan Zhai, Shiqing Ma
2025	J	`jnl`	Successor Clusters: A Behavior Basis for Unsupervised Zero-Shot Reinforcement Learning. Trans. Mach. Learn. Res. Louis Bagot, Lucas Nunes Alegre, Steven Latré, Kevin Mets, Bruno Castro da Silva
2025	J	`jnl`	Which Rewards Matter? Reward Selection for Reinforcement Learning under Limited Feedback. CoRR Shreyas Chaudhari, Renhao Zhang, Philip S. Thomas, Bruno Castro da Silva
2024	J	`jnl`	Abstract Reward Processes: Leveraging State Abstraction for Consistent Off-Policy Evaluation. CoRR Shreyas Chaudhari, Ameet Deshpande, Bruno Castro da Silva, Philip S. Thomas
2024	A*	`conf`	From Past to Future: Rethinking Eligibility Traces. AAAI Dhawal Gupta, Scott M. Jordan, Shreyas Chaudhari, Bo Liu, Philip S. Thomas, Bruno Castro da Silva
2024	J	`jnl`	Mitigating the Curse of Horizon in Monte-Carlo Returns. RLJ Alex Ayoub, David Szepesvari, Francesco Zanini, Bryan Chan, Dhawal Gupta, Bruno Castro da Silva, Dale Schuurmans
2024	A*	`conf`	Position: Benchmarking is Limited in Reinforcement Learning Research. ICML Scott M. Jordan, Adam White, Bruno Castro da Silva, Martha White, Philip S. Thomas
2024	J	`jnl`	Position: Benchmarking is Limited in Reinforcement Learning Research. CoRR Scott M. Jordan, Adam White, Bruno Castro da Silva, Martha White, Philip S. Thomas
2024	J	`jnl`	RLHF Deciphered: A Critical Analysis of Reinforcement Learning from Human Feedback for LLMs. CoRR Shreyas Chaudhari, Pranjal Aggarwal, Vishvak Murahari, Tanmay Rajpurohit, Ashwin Kalyan, Karthik Narasimhan, Ameet Deshpande, Bruno Castro da Silva
2023	J	`jnl`	Behavior Alignment via Reward Function Optimization. CoRR Dhawal Gupta, Yash Chandak, Scott M. Jordan, Philip S. Thomas, Bruno Castro da Silva
2023	J	`jnl`	Coagent Networks: Generalized and Scaled. CoRR James E. Kostas, Scott M. Jordan, Yash Chandak, Georgios Theocharous, Dhawal Gupta, Martha White, Bruno Castro da Silva, Philip S. Thomas
2023	J	`jnl`	From Past to Future: Rethinking Eligibility Traces. CoRR Dhawal Gupta, Scott M. Jordan, Shreyas Chaudhari, Bo Liu, Philip S. Thomas, Bruno Castro da Silva
2023	J	`jnl`	Off-Policy Evaluation for Action-Dependent Non-Stationary Environments. CoRR Yash Chandak, Shiv Shankar, Nathaniel D. Bastian, Bruno Castro da Silva, Emma Brunskill, Philip S. Thomas
2023	—	`conf`	Seldonian Toolkit: Building Software with Safe and Fair Machine Learning. ICSE Companion Austin Hoag, James E. Kostas, Bruno Castro da Silva, Philip S. Thomas, Yuriy Brun
2022	J	`jnl`	Enforcing Delayed-Impact Fairness Guarantees. CoRR Aline Weber, Blossom Metevier, Yuriy Brun, Philip S. Thomas, Bruno Castro da Silva
2022	A*	`conf`	Fairness Guarantees under Demographic Shift. ICLR Stephen Giguere, Blossom Metevier, Bruno Castro da Silva, Yuriy Brun, Philip S. Thomas, Scott Niekum
2022	C	`conf`	Look-Ahead Reinforcement Learning for Load Balancing Network Traffic. ISCC Isadora P. Possebon, Bruno Castro da Silva, Alberto E. Schaeffer-Filho
2022	J	`jnl`	Model-Based Reinforcement Learning with SINDy. CoRR Rushiv Arora, Bruno Castro da Silva, Eliot Moss
2022	—	`conf`	RADAR: Reactive and Deliberative Adaptive Reasoning - Learning When to Think Fast and When to Think Slow. ICDL Ørjan Strand, Didrik Spanne Reilstad, Zhenying Wu, Bruno Castro da Silva, Jim Torresen, Kai Olav Ellefsen
2021	J	`jnl`	Patterns of high-risk drinking among medical students: A web-based survey with machine learning. Comput. Biol. Medicine Grasiela Marcon, Flávia de Ávila Pereira, Aline Zimerman, Bruno Castro da Silva, Lisia von Diemen, Ives Cavalcante Passos, Mariana Recamonde Mendoza
2021	J	`jnl`	Universal Off-Policy Evaluation. CoRR Yash Chandak, Scott Niekum, Bruno Castro da Silva, Erik G. Learned-Miller, Emma Brunskill, Philip S. Thomas
2020	J	`jnl`	Autonomous learning of multiple, context-dependent tasks. CoRR Vieri Giuliano Santucci, Davide Montella, Bruno Castro da Silva, Gianluca Baldassarre
2020	J	`jnl`	Optimal Options for Multi-Task Reinforcement Learning Under Time Constraints. CoRR Manuel Del Verme, Bruno Castro da Silva, Gianluca Baldassarre
2019	B	`conf`	A Methodology for Neural Network Architectural Tuning Using Activation Occurrence Maps. IJCNN Rafael Garcia, Alexandre Xavier Falcão, Alexandru C. Telea, Bruno Castro da Silva, Jim Tørresen, João Luiz Dihl Comba
2019	J	`jnl`	Autonomous Open-Ended Learning of Interdependent Tasks. CoRR Vieri Giuliano Santucci, Emilio Cartoni, Bruno Castro da Silva, Gianluca Baldassarre
2018	J	`jnl`	A task-and-technique centered survey on visual analytics for deep learning model engineering. Comput. Graph. Rafael Garcia, Alexandru C. Telea, Bruno Castro da Silva, Jim Tørresen, João Luiz Dihl Comba
2018	—	`conf`	Efficient Local Memory Support for Approximate Computing. SBESC 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
2018	B	`conf`	Towards Designing Optimal Reward Functions in Multi-Agent Reinforcement Learning Problems. IJCNN Ricardo Grunitzki, Bruno Castro da Silva, Ana L. C. Bazzan
2017	A	`conf`	A Flexible Approach for Designing Optimal Reward Functions. AAMAS Ricardo Grunitzki, Bruno Castro da Silva, Ana L. C. Bazzan
2017	A	`conf`	Context-Based Concurrent Experience Sharing in Multiagent Systems. AAMAS Daniel Garant, Bruno Castro da Silva, Victor R. Lesser, Chongjie Zhang
2017	J	`jnl`	Context-Based Concurrent Experience Sharing in Multiagent Systems. CoRR Daniel Garant, Bruno Castro da Silva, Victor R. Lesser, Chongjie Zhang
2017	A	`conf`	Learning to Minimise Regret in Route Choice. AAMAS Gabriel de Oliveira Ramos, Bruno Castro da Silva, Ana L. C. Bazzan
2017	J	`jnl`	On Ensuring that Intelligent Machines Are Well-Behaved. CoRR Philip S. Thomas, Bruno Castro da Silva, Andrew G. Barto, Emma Brunskill
2017	A	`conf`	Task-based behavior generalization via manifold clustering. IROS Rafael Garcia, Bruno Castro da Silva, João Luiz Dihl Comba
2016	A*	`conf`	Energetic Natural Gradient Descent. ICML Philip S. Thomas, Bruno Castro da Silva, Christoph Dann, Emma Brunskill
2016	—	`conf`	Using Topological Statistics to Bias and Accelerate Route Choice: Preliminary Findings in Synthetic and Real-World Road Networks. ATT@IJCAI Fernando Stefanello, Bruno Castro da Silva, Ana L. C. Bazzan
2014	A*	`conf`	Active Learning of Parameterized Skills. ICML Bruno Castro da Silva, George Dimitri Konidaris, Andrew G. Barto
2014	A*	`conf`	Learning parameterized motor skills on a humanoid robot. ICRA Bruno Castro da Silva, Gianluca Baldassarre, George Dimitri Konidaris, Andrew G. Barto
2013	A	`conf`	Biasing the behavior of organizationally adept agents: (extended abstract). AAMAS Daniel D. Corkill, Chongjie Zhang, Bruno Castro da Silva, Yoonheui Kim, Daniel Garant, Victor R. Lesser, Xiaoqin Zhang
2012	A*	`conf`	Learning Parameterized Skills. ICML Bruno Castro da Silva, George Dimitri Konidaris, Andrew G. Barto
2012	A*	`conf`	TD-DeltaPi: A Model-Free Algorithm for Efficient Exploration. AAAI Bruno Castro da Silva, Andrew G. Barto
2010	J	`jnl`	Learning in groups of traffic signals. Eng. Appl. Artif. Intell. Ana L. C. Bazzan, Denise de Oliveira, Bruno Castro da Silva
2007	A	`conf`	Distributed constraint propagation for diagnosis of faults in physical processes. AAMAS Ana L. C. Bazzan, Bruno Castro da Silva
2006	A*	`conf`	Dealing with non-stationary environments using context detection. ICML Bruno Castro da Silva, Eduardo W. Basso, Ana L. C. Bazzan, Paulo Martins Engel
2006	A	`conf`	ITSUMO: an Intelligent Transportation System for Urban Mobility. AAMAS Bruno Castro da Silva, Robert Junges, Denise de Oliveira, Ana L. C. Bazzan
2006	A	`conf`	Improving reinforcement learning with context detection. AAMAS Bruno Castro da Silva, Eduardo W. Basso, Filipo Studzinski Perotto, Ana L. C. Bazzan, Paulo Martins Engel
2006	A*	`conf`	RL-CD: Dealing with Non-Stationarity in Reinforcement Learning. AAAI Bruno Castro da Silva, Eduardo W. Basso, Ana L. C. Bazzan, Paulo Martins Engel
2006	C	`conf`	Reinforcement Learning based Control of Traffic Lights in Non-stationary Environments: A Case Study in a Microscopic Simulator. EUMAS Denise de Oliveira, Ana L. C. Bazzan, Bruno Castro da Silva, Eduardo W. Basso, Luís Nunes
2004	—	`conf`	ITSUMO: An Intelligent Transportation System for Urban Mobility. IICS Bruno Castro da Silva, Ana L. C. Bazzan, Gustavo Kuhn Andriotti, Filipe Lopes, Denise de Oliveira