Generating Diverse Cooperative Agents by Learning Incompatible Policies R Charakorn, P Manoonpong, N Dilokthanakul International Conference on Learning Representations (ICLR), 𝐒𝐩𝐨𝐭𝐥𝐢𝐠𝐡𝐭, 2023 | 21 | 2023 |
Investigating Partner Diversification Methods in Cooperative Multi-agent Deep Reinforcement Learning R Charakorn, P Manoonpong, N Dilokthanakul International Conference on Neural Information Processing, 395-402, 2020 | 17 | 2020 |
An explicit local and global representation disentanglement framework with applications in deep clustering and unsupervised object detection R Charakorn, Y Thawornwattana, S Itthipuripat, N Pawlowski, ... arXiv preprint arXiv:2001.08957, 2020 | 16 | 2020 |
Learning to Cooperate with Unseen Agents Through Meta-Reinforcement Learning R Charakorn, P Manoonpong, N Dilokthanakul International Conference on Autonomous Agents and MultiAgent Systems (AAMAS …, 2021 | 7 | 2021 |
Open RL Benchmark: Comprehensive Tracked Experiments for Reinforcement Learning S Huang, Q Gallouédec, F Felten, A Raffin, RFJ Dossa, Y Zhao, ... arXiv preprint arXiv:2402.03046, 2024 | 2 | 2024 |
TDD Without Tears: Towards Test Case Generation from Requirements through Deep Reinforcement Learning W Takerngsaksiri, R Charakorn, C Tantithamthavorn, YF Li arXiv preprint arXiv:2401.07576, 2024 | 1 | 2024 |
Cleanba: A Reproducible and Efficient Distributed Reinforcement Learning Platform S Huang, J Weng, R Charakorn, M Lin, Z Xu, S Ontañón International Conference on Learning Representations (ICLR), 2023 | | 2023 |
Pytester: Deep Reinforcement Learning for Text-to-Testcase Generation W Takerngsaksiri, R Charakorn, C Tantithamthavorn, YF Li Available at SSRN 4736450, 0 | | |