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 Conference Papers (Available on Advance Programs)  (Sort by: Date Descending)
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Committee Date Time Place Paper Title / Authors Abstract Paper #
Consen 2025-03-18
15:40		 Hokkaido Humanities and Social Sciences Bldg., Hokkaido University
(Primary: On-site, Secondary: Online)		 Development of Goal-Conditioned Reinforcement Learning Methods Using Sub-Goal Generation by LLM
Eiki Kitagawa, Shiyao Ding, Takayuki Ito (Kyoto Univ.) Consen2024-13		 This study aims to develop an agent capable of understanding task order and dependencies, enabling adaptive responses to... [more] Consen2024-13
pp.36-41
Consen 2024-08-01
13:50		 Kyoto Kyoto University Clock Tower Centennial Hall
(Primary: On-site, Secondary: Online)		 Decision Making in the Era of Large Language Models
Shiyao Ding, Takayuki Ito (Kyoto Univ.) 		 [more]
SWIM, SC 2021-08-27
10:25		 Online Online Combining Multiagent Reinforcement Learning and Discrete Event Modeling for Pathfinding on a Non-Grid Graph
Shiyao Ding (Kyoto Univ.), Hideki Aoyama (Panasonic), Donghui Lin (Kyoto Univ.) SWIM2021-15 SC2021-13		 In this report, we study a new multiagent path finding (MAPF) problem where multiple agents move on a non-grid graph wit... [more] SWIM2021-15 SC2021-13
pp.13-17
MSS, CAS, SIP, VLD 2019-07-31
13:25		 Iwate Iwate Univ. Policy Gradient Lagging Anchor for Concurrent Game
Shiyao Ding, Toshimitsu Ushio (Osaka Univ.) CAS2019-16 VLD2019-22 SIP2019-32 MSS2019-16		  [more] CAS2019-16 VLD2019-22 SIP2019-32 MSS2019-16
pp.67-70
MSS, NLP
(Joint)		 2018-03-12
14:00		 Osaka   Learning in Two-Player Matrix Games by Policy Gradient Lagging Anchor
Shiyao Ding, Toshimitsu Ushio (Osaka Univ.) MSS2017-79		 We propose a novel multi-agent reinforcement learning (MARL) algorithm which is called a policy gra-
dient lagging anch... [more]		 MSS2017-79
pp.11-14
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