[2Q4-OS-27b] 強化学習の新展開

Wed. Jun 7, 2023 1:30 PM - 3:10 PM Room Q (601)

オーガナイザ：太田宏之、甲野佑、高橋達二

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1:30 PM - 1:50 PM

[2Q4-OS-27b-01] A unified control mechanism for action planning, execution, dialogue, and inference for the reward maximization

〇Yuuji Ichisugi¹, Hidemoto Nakada¹, Naoto Takahashi¹, Izumi Takeuti¹, Takashi Sano² (1. AIST, 2. Toyo University)

[[Online]]

1:50 PM - 2:10 PM

[2Q4-OS-27b-02] Target-oriented Exploration in Deep Reinforcement Learning

〇Yu Kono^1,2, Jun Kume¹, Ikeda Ryuji³, Tatsuji Takahashi¹ (1. Tokyo Denki University, School of Science and Engineering, 2. DeNA Co., Ltd., 3. Graduate School of Tokyo Denki University)

2:10 PM - 2:30 PM

[2Q4-OS-27b-03] Emulation in reinforcement learning

〇Reina Kitade¹, Takuma Wada², Yu Kono¹, Tatsuji Takahashi¹ (1. Tokyo Denki University, 2. Graduate School of Tokyo Denki University)

2:30 PM - 2:50 PM

[2Q4-OS-27b-04] Expansion to Gaussian Distributional Rewards in Natural Reinforcement Learning

〇Shoma Ogawa¹, Shuichi Arimura², Tatsuji Takahashi¹, Yu Kohno¹ (1. School of Science and Engineering, Tokyo Denki University, 2. Graduate School of Tokyo Denki University)

2:50 PM - 3:10 PM

[2Q4-OS-27b-05] Top-level battle AI of The Modern Mobile Game "Gyakuten Othellonia" by Using Reinforcement Learning

〇Katsuki Ohto Ohto¹, Yuta Goto², Yu Kono¹, Ikki Tanaka¹ (1. DeNA Co., Ltd., 2. Tokyo University of Agriculture and Technology)

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