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Between MDPs and Semi-MDPs: learning, planning, and representing knowledge at multiple temporal scales, , and . 98-74. University of Massachusetts, Amherst, MA 01003, (1998)Near-optimal reinforcement learning in polynomial time, and . Proc. 15th International Conf. on Machine Learning, page 260--268. Morgan Kaufmann, San Francisco, CA, (1998)Bootstrapped Meta-Learning, , , , , and . (2021)cite arxiv:2109.04504Comment: 31 pages, 19 figures, 7 tables.Blockchain and Deep Learning for Secure Communication in Digital Twin Empowered Industrial IoT Network., , , , , and . IEEE Trans. Netw. Sci. Eng., 10 (5): 2802-2813 (September 2023)Multi-task seizure detection: addressing intra-patient variation in seizure morphologies., , , , and . Mach. Learn., 102 (3): 309-321 (2016)Deep Reinforcement Learning for Multi-driver Vehicle Dispatching and Repositioning Problem., , , , , , , , and . ICDM, page 1090-1095. IEEE, (2019)Building a Motivational Interviewing Dataset., , , , and . CLPsych@HLT-NAACL, page 42-51. The Association for Computational Linguistics, (2016)Intelligent Reflecting Surface-based Secrecy Rate Enhancement in Multicast Multigroup Tactical Communication Systems., , and . MILCOM, page 769-774. IEEE, (2022)Joint Jamming Alleviation for Mixed RF/FSO Relay Networks: Optimization and Learning Approaches., , , , and . MILCOM, page 450-455. IEEE, (2023)Reinforcement Learning for Sparse-Reward Object-Interaction Tasks in a First-person Simulated 3D Environment., , , , , , and . IJCAI, page 2219-2226. ijcai.org, (2021)