Gabriel de Oliveira Ramos

Publication Activity (10 Years)

Years Active: 2013-2024
Publications (10 Years): 46

Top Topics

Traffic Assignment

Reward Function

Reinforcement Learning

Top Venues

Publications

Vitor A. Fraga, Lincoln Vinicius Schreiber, Marco Antonio Chitolina Da Silva, Rafael Kunst, Jorge L. V. Barbosa, Gabriel de Oliveira Ramos
A machine learning pipeline for extracting decision-support features from traffic scenes. AI Commun. 37 (2) (2024)
Peter Vamplew, Cameron Foale, Conor F. Hayes, Patrick Mannion, Enda Howley, Richard Dazeley, Scott Johnson, Johan Källström, Gabriel de Oliveira Ramos, Roxana Radulescu, Willem Röpke, Diederik M. Roijers
Utility-Based Reinforcement Learning: Unifying Single-objective and Multi-objective Reinforcement Learning. CoRR (2024)
Felipe André Zeiser, Cristiano André da Costa, Gabriel de Oliveira Ramos, Andreas K. Maier, Rodrigo da Rosa Righi
CheXReport: A transformer-based architecture to generate chest X-ray reports suggestions. Expert Syst. Appl. 255 (2024)
Peter Vamplew, Cameron Foale, Conor F. Hayes, Patrick Mannion, Enda Howley, Richard Dazeley, Scott Johnson, Johan Källström, Gabriel de Oliveira Ramos, Roxana Radulescu, Willem Röpke, Diederik M. Roijers
Utility-Based Reinforcement Learning: Unifying Single-objective and Multi-objective Reinforcement Learning. AAMAS (2024)
Gefersom Lima, Felipe André Zeiser, Ariane da Silveira, Sandro Rigo, Gabriel de Oliveira Ramos
An encoder-decoder deep neural network for binary segmentation of seismic facies. Comput. Geosci. 183 (2024)
Luis Antonio Leite Francisco da Costa, Mateus Begnini Melchiades, Valéria Soldera Girelli, Felipe Colombelli, Denis Andrei de Araújo, Sandro José Rigo, Gabriel de Oliveira Ramos, Cristiano André da Costa, Rodrigo da Rosa Righi, Jorge Luis Victória Barbosa
Advancing Chatbot Conversations: A Review of Knowledge Update Approaches. J. Braz. Comput. Soc. 30 (1) (2024)
Marcos Leandro Hoffmann Souza, Cristiano André da Costa, Gabriel de Oliveira Ramos
A machine-learning based data-oriented pipeline for Prognosis and Health Management Systems. Comput. Ind. 148 (2023)
Felipe André Zeiser, Ismael Santos, Henrique Bohn, Cristiano André da Costa, Gabriel de Oliveira Ramos, Rodrigo da Rosa Righi, Andreas Maier, José Rodrigo M. Andrade, Alexandre Bacelar
Pleural Effusion Classification on Chest X-Ray Images with Contrastive Learning. WEBIST (2023)
Conor F. Hayes, Roxana Radulescu, Eugenio Bargiacchi, Johan Källström, Matthew Macfarlane, Mathieu Reymond, Timothy Verstraeten, Luisa M. Zintgraf, Richard Dazeley, Fredrik Heintz, Enda Howley, Athirai A. Irissappane, Patrick Mannion, Ann Nowé, Gabriel de Oliveira Ramos, Marcello Restelli, Peter Vamplew, Diederik M. Roijers
A Brief Guide to Multi-Objective Reinforcement Learning and Planning. AAMAS (2023)
Juarez Machado da Silva, Gabriel de Oliveira Ramos, Jorge Luis Victória Barbosa
Multi-Objective Decision-Making Meets Dynamic Shortest Path: Challenges and Prospects. Algorithms 16 (3) (2023)
Peter Vamplew, Benjamin J. Smith, Johan Källström, Gabriel de Oliveira Ramos, Roxana Radulescu, Diederik M. Roijers, Conor F. Hayes, Friedrik Hentz, Patrick Mannion, Pieter J. K. Libin, Richard Dazeley, Cameron Foale
Scalar Reward is Not Enough. AAMAS (2023)
Tiago Boechel, Lucas Micol Policarpo, Gabriel de Oliveira Ramos, Rodrigo da Rosa Righi, Dhananjay Singh
Prediction of Harvest Time of Apple Trees: An RNN-Based Approach. Algorithms 15 (3) (2022)
Jovani Dalzochio, Rafael Kunst, Jorge Luis Victória Barbosa, Henrique Damasceno Vianna, Gabriel de Oliveira Ramos, Edison Pignaton, Alécio P. D. Binotto, Jose Favilla
ELFpm: A machine learning framework for industrial machines prediction of remaining useful life. Neurocomputing 512 (2022)
Luana Carine Schünke, Blanda Mello, Cristiano André da Costa, Rodolfo Stoffel Antunes, Sandro José Rigo, Gabriel de Oliveira Ramos, Rodrigo da Rosa Righi, Juliana Nichterwitz Scherer, Bruna Donida
A rapid review of machine learning approaches for telemedicine in the scope of COVID-19. Artif. Intell. Medicine 129 (2022)
Lucas M. Ceschini, Lucas Micol Policarpo, Rodrigo da Rosa Righi, Gabriel de Oliveira Ramos
Aiding Glaucoma Diagnosis from the Automated Classification and Segmentation of Fundus Images. BRACIS (2) (2022)
Bruno Grisci, Gabriela Kuhn, Felipe Colombelli, Vítor Kehl Matter, Leomar Lima, Karine Heinen, Mauricio Pegoraro, Marcio Borges, Sandro Rigo, Jorge L. V. Barbosa, Rodrigo da Rosa Righi, Cristiano André da Costa, Gabriel de Oliveira Ramos
Perspectives on risk prioritization of data center vulnerabilities using rank aggregation and multi-objective optimization. CoRR (2022)
João Batista Rodrigues Neto, Gabriel de Oliveira Ramos
An Interpolated Approach for Active Debris Removal. CEC (2022)
Felipe Colombelli, Vítor Kehl Matter, Bruno Iochins Grisci, Leomar Lima, Karine Heinen, Marcio Borges, Sandro José Rigo, Jorge Luis Victória Barbosa, Rodrigo da Rosa Righi, Cristiano André da Costa, Gabriel de Oliveira Ramos
Multi-objective prioritization for data center vulnerability remediation. CEC (2022)
Juarez Machado da Silva, Gabriel de Oliveira Ramos, Jorge L. V. Barbosa
The multi-objective dynamic shortest path problem. CEC (2022)
Arturo de Souza, Mateus Begnini Melchiades, Sandro José Rigo, Gabriel de Oliveira Ramos
MoStress: a Sequence Model for Stress Classification. IJCNN (2022)
Samuel A. Freitas, Felipe André Zeiser, Cristiano André da Costa, Gabriel de Oliveira Ramos
DeepCADD: A Deep Learning Architecture for Automatic Detection of Coronary Artery Disease. IJCNN (2022)
Peter Vamplew, Benjamin J. Smith, Johan Källström, Gabriel de Oliveira Ramos, Roxana Radulescu, Diederik M. Roijers, Conor F. Hayes, Fredrik Heintz, Patrick Mannion, Pieter J. K. Libin, Richard Dazeley, Cameron Foale
Scalar reward is not enough: a response to Silver, Singh, Precup and Sutton (2021). Auton. Agents Multi Agent Syst. 36 (2) (2022)
Lincoln Vinicius Schreiber, Lucas Nunes Alegre, Ana L. C. Bazzan, Gabriel de Oliveira Ramos
On the Explainability and Expressiveness of Function Approximation Methods in RL-Based Traffic Signal Control. IJCNN (2022)
Conor F. Hayes, Roxana Radulescu, Eugenio Bargiacchi, Johan Källström, Matthew Macfarlane, Mathieu Reymond, Timothy Verstraeten, Luisa M. Zintgraf, Richard Dazeley, Fredrik Heintz, Enda Howley, Athirai A. Irissappane, Patrick Mannion, Ann Nowé, Gabriel de Oliveira Ramos, Marcello Restelli, Peter Vamplew, Diederik M. Roijers
A practical guide to multi-objective reinforcement learning and planning. Auton. Agents Multi Agent Syst. 36 (1) (2022)
Igor Felipe de Camargo, Rodolfo Stoffel Antunes, Gabriel de Oliveira Ramos
On Social Consensus Mechanisms for Federated Learning Aggregation. BRACIS (2) (2022)
Nícolas B. Santos, Rodrigo Simon Bavaresco, João Elison da Rosa Tavares, Gabriel de Oliveira Ramos, Jorge L. V. Barbosa
A systematic mapping study of robotics in human care. Robotics Auton. Syst. 144 (2021)
João Batista Rodrigues Neto, Gabriel de Oliveira Ramos
An Enhanced TSP-Based Approach for Active Debris Removal Mission Planning. BRACIS (1) (2021)
Conor F. Hayes, Roxana Radulescu, Eugenio Bargiacchi, Johan Källström, Matthew Macfarlane, Mathieu Reymond, Timothy Verstraeten, Luisa M. Zintgraf, Richard Dazeley, Fredrik Heintz, Enda Howley, Athirai A. Irissappane, Patrick Mannion, Ann Nowé, Gabriel de Oliveira Ramos, Marcello Restelli, Peter Vamplew, Diederik M. Roijers
A Practical Guide to Multi-Objective Reinforcement Learning and Planning. CoRR (2021)
Peter Vamplew, Benjamin J. Smith, Johan Källström, Gabriel de Oliveira Ramos, Roxana Radulescu, Diederik M. Roijers, Conor F. Hayes, Fredrik Heintz, Patrick Mannion, Pieter J. K. Libin, Richard Dazeley, Cameron Foale
Scalar reward is not enough: A response to Silver, Singh, Precup and Sutton (2021). CoRR (2021)
Marcos Leandro Hoffmann Souza, Cristiano André da Costa, Gabriel de Oliveira Ramos, Rodrigo da Rosa Righi
A feature identification method to explain anomalies in condition monitoring. Comput. Ind. 133 (2021)
Felipe André Zeiser, Cristiano André da Costa, Gabriel de Oliveira Ramos, Henrique Bohn, Ismael Santos, Rodrigo da Rosa Righi
Evaluation of Convolutional Neural Networks for COVID-19 Classification on Chest X-Rays. CoRR (2021)
Felipe André Zeiser, Cristiano André da Costa, Gabriel de Oliveira Ramos, Henrique Bohn, Ismael Santos, Rodrigo da Rosa Righi
Evaluation of Convolutional Neural Networks for COVID-19 Classification on Chest X-Rays. BRACIS (2) (2021)
Tiago Boechel, Lucas Micol Policarpo, Gabriel de Oliveira Ramos, Rodrigo da Rosa Righi
Fuzzy time series for predicting phenological stages of apple trees. SAC (2021)
Felipe André Zeiser, Cristiano André da Costa, Gabriel de Oliveira Ramos, Henrique Bohn, Ismael Santos, Adriana Vial Roehe
: A hybrid deep learning model for interpretable diagnosis of breast cancer in whole-slide images. Expert Syst. Appl. 185 (2021)
Miromar José de Lima, César David Paredes Crovato, Rodrigo Ivan Goytia Mejia, Rodrigo da Rosa Righi, Gabriel de Oliveira Ramos, Cristiano André da Costa, Giovani Pesenti
HealthMon: An approach for monitoring machines degradation using time-series decomposition, clustering, and metaheuristics. Comput. Ind. Eng. 162 (2021)
Ricardo Grunitzki, Gabriel de Oliveira Ramos
On the Role of Reward Functions for Reinforcement Learning in the Traffic Assignment Problem. IJCNN (2020)
Gabriel de Oliveira Ramos, Bruno C. da Silva, Roxana Radulescu, Ana L. C. Bazzan, Ann Nowé
Toll-based reinforcement learning for efficient equilibria in route choice. Knowl. Eng. Rev. 35 (2020)
Gabriel Souto Fischer, Rodrigo da Rosa Righi, Gabriel de Oliveira Ramos, Cristiano André da Costa, Joel J. P. C. Rodrigues
ElHealth: Using Internet of Things and data prediction for elastic management of human resources in smart hospitals. Eng. Appl. Artif. Intell. 87 (2020)
Gabriel de Oliveira Ramos, Roxana Radulescu, Ann Nowé, Anderson R. Tavares
Toll-Based Learning for Minimising Congestion under Heterogeneous Preferences. AAMAS (2020)
Bruno Klein Salvalaio, Gabriel de Oliveira Ramos
Self-Adaptive Appearance-Based Eye-Tracking with Online Transfer Learning. BRACIS (2019)
Lucas Oliveira Souza, Gabriel de Oliveira Ramos, Célia Ghedini Ralha
Experience Sharing Between Cooperative Reinforcement Learning Agents. ICTAI (2019)
Lucas Oliveira Souza, Gabriel de Oliveira Ramos, Célia Ghedini Ralha
Experience Sharing Between Cooperative Reinforcement Learning Agents. CoRR (2019)
Gabriel de Oliveira Ramos
Minimising Regret in Route Choice. AAMAS (2017)
Gabriel de Oliveira Ramos, Bruno Castro da Silva, Ana L. C. Bazzan
Learning to Minimise Regret in Route Choice. AAMAS (2017)
Gabriel de Oliveira Ramos, Ana L. C. Bazzan
Efficient local search in traffic assignment. CEC (2016)
Gabriel de Oliveira Ramos, Ana L. C. Bazzan
On Estimating Action Regret and Learning From It in Route Choice. ATT@IJCAI (2016)
Gabriel de Oliveira Ramos, Juan C. Burguillo, Ana L. C. Bazzan
A self-adapting similarity-based coalition formation approach for plug-in electric vehicles in smart grids. Multiagent Grid Syst. 11 (3) (2015)
Gabriel de Oliveira Ramos, Ana Lúcia Cetertich Bazzan
Towards the User Equilibrium in Traffic Assignment Using GRASP with Path Relinking. GECCO (2015)
Ana L. C. Bazzan, Gabriel de Oliveira Ramos
Forming Coalitions of Electric Vehicles in Constrained Scenarios. PAAMS (Workshops) (2015)
Ricardo Grunitzki, Gabriel de Oliveira Ramos, Ana Lúcia C. Bazzan
Individual versus Difference Rewards on Reinforcement Learning for Route Choice. BRACIS (2014)
Gabriel de Oliveira Ramos, Ricardo Grunitzki
An Improved Learning Automata Approach for the Route Choice Problem. ARE/AVSA@AAMAS (2014)
Gabriel de Oliveira Ramos, Juan C. Burguillo, Ana L. C. Bazzan
Dynamic constrained coalition formation among electric vehicles. J. Braz. Comput. Soc. 20 (1) (2014)
Gabriel de Oliveira Ramos, Juan C. Burguillo-Rial, Ana L. C. Bazzan
Self-Adapting Coalition Formation Among Electric Vehicles in Smart Grids. SASO (2013)
Andrew Koster, Gabriel de Oliveira Ramos, Ana L. C. Bazzan, Fernando Koch
Towards a Platform for Testing and Developing Privacy-Preserving Data Mining Applications for Smart Grids. MATES (2013)