| Evolution-guided policy gradient in reinforcement learning S Khadka, K Tumer Advances in Neural Information Processing Systems 31, 2018 | 297* | 2018 |
| Collaborative evolutionary reinforcement learning S Khadka, S Majumdar, T Nassar, Z Dwiel, E Tumer, S Miret, Y Liu, ... Proceedings of the International Conference on Machine Learning, 3341-3350, 2019 | 140 | 2019 |
| Evolutionary reinforcement learning for sample-efficient multiagent coordination S Majumdar, S Khadka, S Miret, S McAleer, K Tumer International Conference on Machine Learning, 6651-6660, 2020 | 63 | 2020 |
| Artificial intelligence for prosthetics: Challenge solutions Ł Kidziński, C Ong, SP Mohanty, J Hicks, S Carroll, B Zhou, H Zeng, ... The NeurIPS'18 Competition: From Machine Learning to Intelligent …, 2020 | 46 | 2020 |
| Evolving memory-augmented neural architecture for deep memory problems S Khadka, JJ Chung, K Tumer Proceedings of the Genetic and Evolutionary Computation Conference, 441-448, 2017 | 18 | 2017 |
| Neuroevolution of a modular memory-augmented neural network for deep memory problems S Khadka, JJ Chung, K Tumer Evolutionary computation 27 (4), 639-664, 2019 | 15 | 2019 |
| Optimizing memory placement using evolutionary graph reinforcement learning S Khadka, E Aflalo, M Marder, A Ben-David, S Miret, S Mannor, T Hazan, ... arXiv preprint arXiv:2007.07298, 2020 | 14 | 2020 |
| Learning intrinsic symbolic rewards in reinforcement learning HU Sheikh, S Khadka, S Miret, S Majumdar, M Phielipp 2022 International Joint Conference on Neural Networks (IJCNN), 1-8, 2022 | 13 | 2022 |
| Multi-level fitness critics for cooperative coevolution G Rockefeller, S Khadka, K Tumer AAMAS Conference proceedings, 2020 | 13 | 2020 |
| Maedys: Multiagent evolution via dynamic skill selection E Sachdeva, S Khadka, S Majumdar, K Tumer Proceedings of the Genetic and Evolutionary Computation Conference, 163-171, 2021 | 7 | 2021 |
| A memory-based multiagent framework for adaptive decision making S Khadka, C Yates, K Tumer Proceedings of the 17th International Conference on Autonomous Agents and …, 2018 | 6 | 2018 |
| Neuroevolution of a hybrid power plant simulator S Khadka, K Tumer, M Colby, D Tucker, P Pezzini, K Bryden Proceedings of the Genetic and Evolutionary Computation Conference 2016, 917-924, 2016 | 6 | 2016 |
| Memory-augmented multi-robot teams that learn to adapt S Khadka, JJ Chung, K Tumer 2017 International Symposium on Multi-Robot and Multi-Agent Systems (MRS …, 2017 | 4 | 2017 |
| Dynamic skill selection for learning joint actions E Sachdeva, S Khadka Autonomous agents and multiagent systems, 2021 | 1 | 2021 |
| Automatic multi-objective hardware optimization for processing of deep learning networks M Marder, E Aflalo, A Ben-David, S Khadka, S Majumdar, S Miret, H Tang US Patent App. 17/129,521, 2021 | | 2021 |
| Memory-Based Multiagent One-Shot Learning S Khadka, C Yates, K Tumer 2019 International Symposium on Multi-Robot and Multi-Agent Systems (MRS …, 2019 | | 2019 |
| Tackling Credit Assignment Using Memory and Multilevel Optimization for Multiagent Reinforcement Learning S Khadka | | 2019 |
| Fabrication of Oxygenation Microfluidic Devices for Cell Cultures DTE Shauharda Khadka, Gerardo Mauleon Journal of Undergraduate Research 7 (1), 5-9, 2014 | | 2014 |
| Optimizing Multiagent Cooperation via Policy Evolution and Shared Experiences S Majumdar, S Khadka, S Miret, S Mcaleer, K Tumer | | |
Kagan TumerOregon State University在 oregonstate.edu 的电子邮件经过验证
