| Simultaneously Learning and Advising in Multiagent Reinforcement Learning FL da Silva, R Glatt, AHR Costa Proc. 16th International Conference on Autonomous Agents and Multiagent …, 2017 | 149 | 2017 |
| Symbolic Regression via Neural-Guided Genetic Programming Population Seeding T Mundhenk, M Landajuela, R Glatt, C Santiago, B Petersen Advances in Neural Information Processing Systems 34, 2021 | 99* | 2021 |
| Discovering symbolic policies with deep reinforcement learning M Landajuela, BK Petersen, S Kim, CP Santiago, R Glatt, N Mundhenk, ... International Conference on Machine Learning, 5979-5989, 2021 | 92 | 2021 |
| Towards Knowledge Transfer in Deep Reinforcement Learning R Glatt, FL Silva, AHR Costa 5th Brazilian Conference on Intelligent System (BRACIS), 91-96, 2016 | 52 | 2016 |
| MOO-MDP: An Object-Oriented Representation for Cooperative Multiagent Reinforcement Learning FL Da Silva, R Glatt, AHR Costa IEEE Transactions on Cybernetics 49 (2), 567-579, 2019 | 38 | 2019 |
| A Unified Framework for Deep Symbolic Regression M Landajuela, C Lee, J Yang, R Glatt, CP Santiago, I Aravena, ... Advances in Neural Information Processing Systems, 2022 | 33 | 2022 |
| Decaf: deep case-based policy inference for knowledge transfer in reinforcement learning R Glatt, FL Da Silva, RA da Costa Bianchi, AHR Costa Expert Systems with Applications 156, 113420, 2020 | 27 | 2020 |
| Increasing performance of electric vehicles in ride-hailing services using deep reinforcement learning JF Pettit, R Glatt, JR Donadee, BK Petersen arXiv preprint arXiv:1912.03408, 2019 | 19 | 2019 |
| Improving exploration in policy gradient search: Application to symbolic optimization M Landajuela, BK Petersen, SK Kim, CP Santiago, R Glatt, TN Mundhenk, ... arXiv e-prints, arXiv: 2107.09158, 2021 | 16* | 2021 |
| Collaborative energy demand response with decentralized actor and centralized critic R Glatt, FL Silva, B Soper, WA Dawson, E Rusu, RA Goldhahn International Conference on Systems for Energy-Efficient Buildings, Cities …, 2021 | 11 | 2021 |
| Deep Symbolic Optimization for Electric Component Sizing in Fixed Topology Power Converters R Glatt, FL Silva, C Huang, L Xue, M Wang, F Chang, V Bui, YL Murphey, ... Lawrence Livermore National Lab.(LLNL), Livermore, CA (United States), 2021 | 11 | 2021 |
| Improving Deep Reinforcement Learning with knowledge transfer (Extended abstract) R Glatt, AHR Costa Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence …, 2017 | 11* | 2017 |
| Policy Reuse in Deep Reinforcement Learning (Student abstract) R Glatt, AHR Costa Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence …, 2017 | 10* | 2017 |
| Case-based Policy Inference for Transfer in Reinforcement Learning R Glatt, FL Silva, AHR Costa Workshop on Scaling-Up Reinforcement Learning (SURL) at the 28th European …, 2017 | 8 | 2017 |
| An intelligent system for automatic selection of dc-dc converter topology with optimal design S Wang, Y Murphey, W Su, M Wang, V Bui, F Chang, C Huang, L Xue, ... Lawrence Livermore National Lab.(LLNL), Livermore, CA (United States), 2022 | 7 | 2022 |
| Interpretable symbolic regression for data science: Analysis of the 2022 competition FO de França, M Virgolin, M Kommenda, MS Majumder, M Cranmer, ... arXiv preprint arXiv:2304.01117, 2023 | 6 | 2023 |
| Deep neural network-based surrogate model for optimal component sizing of power converters using deep reinforcement learning VH Bui, F Chang, W Su, M Wang, YL Murphey, FL Da Silva, C Huang, ... IEEE Access 10, 78702-78712, 2022 | 6 | 2022 |
| A study on efficient reinforcement learning through knowledge transfer R Glatt, FL da Silva, RA da Costa Bianchi, AHR Costa Federated and Transfer Learning, 329-356, 2022 | 4 | 2022 |
| A Framework to Discover and Reuse Object-Oriented Options in Reinforcement Learning RC Bonini, FL da Silva, R Glatt, E Spina, AHR Costa 7th Brazilian Conference on Intelligent Systems (BRACIS), 2018 | 4 | 2018 |
| Leveraging Language Models to Efficiently Learn Symbolic Optimization Solutions FL da Silva, A Goncalves, S Nguyen, D Vashchenko, R Glatt, T Desautels, ... Adaptive and Learning Agents Workshop 2022, 2022 | 3 | 2022 |
Felipe Leno da Silva (Leno)Lawrence Livermore National LabBestätigte E-Mail-Adresse bei llnl.gov
