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14. Kozuno, Tadashi, Efficient and Noise-Tolerant Reinforcement Learning Algorithms via Theoretical Analysis of Gap-Increasing and Softmax Operators, 2020, Dissertation BibTeX
15. Takashi Ikegami, 傀儡神楽, TOKYO ALIFE 2020 ver.0, 2020, Tokyo, Japan, Performance BibTeX
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19. Parmas, Paavo, Total stochastic gradient algorithms and applications to model-based reinforcement learning, 2020, Dissertation BibTeX