A reference process for automating bee species identification based on wing images and digital image processing. - Fabiana Soares Santana; Anna Helena Reali Costa; Flavio Sales Truzzi; Felipe Leno da Silva; Sheila L. Santos; Tiago Mauricio Francoy; Antonio Mauro Saraiva (Ecol. Informatics, 2014)

Evaluating classification and feature selection techniques for honeybee subspecies identification using wing images. - Felipe Leno da Silva; Marina Lopes Grassi Sella; Tiago Mauricio Francoy; Anna Helena Reali Costa (Comput. Electron. Agric., 2015)

Towards Knowledge Transfer in Deep Reinforcement Learning. - Ruben Glatt; Felipe Leno da Silva; Anna Helena Reali Costa (BRACIS, 2016)

Object-Oriented Reinforcement Learning in Cooperative Multiagent Domains. - Felipe Leno da Silva; Ruben Glatt; Anna Helena Reali Costa (BRACIS, 2016)

A Framework for Scalable Inference of Temporal Gene Regulatory Networks based on Clustering and Multivariate Analysis. - Ricardo de Souza Jacomini; David Correa Martins Jr.; Felipe Leno da Silva; Anna Helena Reali Costa (BAI@IJCAI, 2016)

Transfer Learning for Multiagent Reinforcement Learning Systems. - Felipe Leno da Silva; Anna Helena Reali Costa (IJCAI, 2016)

Learning Options in Multiobjective Reinforcement Learning. - Rodrigo Cesar Bonini; Felipe Leno da Silva; Anna Helena Reali Costa (AAAI, 2017)

Using Options to Accelerate Learning of New Tasks According to Human Preferences. - Rodrigo Cesar Bonini; Felipe Leno da Silva; Edison Spina; Anna Helena Reali Costa (AAAI Workshops, 2017)

Accelerating Multiagent Reinforcement Learning through Transfer Learning. - Felipe Leno da Silva; Anna Helena Reali Costa (AAAI, 2017)

An Advising Framework for Multiagent Reinforcement Learning Systems. - Felipe Leno da Silva; Ruben Glatt; Anna Helena Reali Costa (AAAI, 2017)

Simultaneously Learning and Advising in Multiagent Reinforcement Learning. - Felipe Leno da Silva; Ruben Glatt; Anna Helena Reali Costa (AAMAS, 2017)

GeNICE: A Novel Framework for Gene Network Inference by Clustering, Exhaustive Search, and Multivariate Analysis. - Ricardo de Souza Jacomini; David Correa Martins Jr.; Felipe Leno da Silva; Anna Helena Reali Costa (J. Comput. Biol., 2017)

Performance Evaluation of Cryptographic Algorithms over IoT Platforms and Operating Systems. - Geovandro C. C. F. Pereira; Renan C. A. Alves; Felipe Leno da Silva; Roberto M. Azevedo; Bruno C. Albertini; Cíntia B. Margi (Secur. Commun. Networks, 2017)

Object-Oriented Curriculum Generation for Reinforcement Learning. - Felipe Leno da Silva; Anna Helena Reali Costa (AAMAS, 2018)

A Framework to Discover and Reuse Object-Oriented Options in Reinforcement Learning. - Rodrigo Cesar Bonini; Felipe Leno da Silva; Ruben Glatt; Edison Spina; Anna Helena Reali Costa (BRACIS, 2018)

Autonomously Reusing Knowledge in Multiagent Reinforcement Learning. - Felipe Leno da Silva; Matthew E. Taylor; Anna Helena Reali Costa (IJCAI, 2018)

Pairwise registration in indoor environments using adaptive combination of 2D and 3D cues. - Juan Carlos Perafan Villota; Felipe Leno da Silva; Ricardo de Souza Jacomini; Anna Helena Reali Costa (Image Vis. Comput., 2018)

Integrating Agent Advice and Previous Task Solutions in Multiagent Reinforcement Learning. - Felipe Leno da Silva (AAMAS, 2019)

Building Self-Play Curricula Online by Playing with Expert Agents in Adversarial Games. - Felipe Leno da Silva; Anna Helena Reali Costa; Peter Stone 001 (BRACIS, 2019)

A Survey on Transfer Learning for Multiagent Reinforcement Learning Systems. - Felipe Leno da Silva; Anna Helena Reali Costa (J. Artif. Intell. Res., 2019)

MOO-MDP: An Object-Oriented Representation for Cooperative Multiagent Reinforcement Learning. - Felipe Leno da Silva; Ruben Glatt; Anna Helena Reali Costa (IEEE Trans. Cybern., 2019)

Providing Uncertainty-Based Advice for Deep Reinforcement Learning Agents (Student Abstract). - Felipe Leno da Silva; Pablo Hernandez-Leal; Bilal Kartal; Matthew E. Taylor (AAAI, 2020)

Uncertainty-Aware Action Advising for Deep Reinforcement Learning Agents. - Felipe Leno da Silva; Pablo Hernandez-Leal; Bilal Kartal; Matthew E. Taylor (AAAI, 2020)

Agents teaching agents: a survey on inter-agent transfer learning. - Felipe Leno da Silva; Garrett Warnell; Anna Helena Reali Costa; Peter Stone 001 (Auton. Agents Multi Agent Syst., 2020)

DECAF: Deep Case-based Policy Inference for knowledge transfer in Reinforcement Learning. - Ruben Glatt; Felipe Leno da Silva; Reinaldo Augusto da Costa Bianchi; Anna Helena Reali Costa (Expert Syst. Appl., 2020)

Coordination of Electric Vehicle Charging Through Multiagent Reinforcement Learning. - Felipe Leno da Silva; Cyntia Eico Hayama Nishida; Diederik M. Roijers; Anna Helena Reali Costa (IEEE Trans. Smart Grid, 2020)

Designing a Hybrid AI Residency. - Felipe Leno da Silva; Silvio Stanzani; Jefferson Fialho; Jorge Mondadori; Muriel Mazzetto; Felipe Sanches Couto; Raphael Cóbe (AAAI, 2021)

Collaborative energy demand response with decentralized actor and centralized critic. - Ruben Glatt; Felipe Leno da Silva; Braden Soper; William A. Dawson; Edward Rusu; Ryan A. Goldhahn (BuildSys, 2021)

Transfer Learning for Multiagent Reinforcement Learning Systems - Felipe Leno da Silva; Anna Helena Reali Costa (Morgan & Claypool Publishers, 2021)

Deep Neural Network-Based Surrogate Model for Optimal Component Sizing of Power Converters Using Deep Reinforcement Learning. - Van-Hai Bui; Fangyuan Chang; Wencong Su; Mengqi Wang; Yi Lu Murphey; Felipe Leno da Silva; Can Huang; Lingxiao Xue; Ruben Glatt (IEEE Access, 2022)

Special issue on adaptive and learning agents 2020. - Felipe Leno da Silva; Patrick MacAlpine; Roxana Radulescu; Fernando P. Santos; Patrick Mannion (Neural Comput. Appl., 2022)

Deep Reinforcement Learning-Based Optimal Parameter Design of Power Converters. - Van-Hai Bui; Fangyuan Chang; Wencong Su; Mengqi Wang; Yi Lu Murphey; Felipe Leno da Silva; Can Huang; Lingxiao Xue; Ruben Glatt (ICNC, 2023)

A Review on Simulation Platforms for Agent-Based Modeling in Electrified Transportation. - Donté Harris; Felipe Leno da Silva; Wencong Su; Ruben Glatt (IEEE Trans. Intell. Transp. Syst., 2024)

Deep Symbolic Optimization: Reinforcement Learning for Symbolic Mathematics. - Conor F. Hayes; Felipe Leno da Silva; Jiachen Yang; T. Nathan Mundhenk; Chak Shing Lee; Jacob F. Pettit; Claudio Santiago; Sookyung Kim; Joanne Taery Kim; Ignacio Aravena Solis; Ruben Glatt; Andre R. Goncalves; et al. (CoRR, 2025)