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 Conference Papers (Available on Advance Programs)  (Sort by: Date Descending)
 Results 1 - 6 of 6  /   
Committee Date Time Place Paper Title / Authors Abstract Paper #
AI 2021-02-22
14:40
Online Online A Study on the Application of Curriculum Learning in Deep Reinforcement Learning -- action acquisition in shooting game AI as an example --
Ikumi Kodaka, Fumiaki Saito (CIT) AI2020-47
Deep reinforcement learning is attracting attention because it can be applied to higher-dimensional environments compare... [more] AI2020-47
pp.47-52
IN 2021-01-19
10:55
Online Online A Study on Humanization Elements for Enabling Game AI to Behave Human-like in Othello
Yuta Yoshida, Komei Arasawa, Shun Hattori (Muroran Inst. of Tech.) IN2020-51
Currently, there are researches on the "strength" of game AIs in various games. In previous researches, a game AI's beha... [more] IN2020-51
pp.43-48
IN 2021-01-19
11:20
Online Online A Study on AI's Degree of General Purpose Towards Realizing AGI by Adaptive Selection of Narrow AIs
Masumi Kurono, Komei Arasawa, Shun Hattori (Muroran Inst. of Tech.) IN2020-52
As the performance of computers has improved, many researches on Artificial Intelligence (AI) have been conducted as an ... [more] IN2020-52
pp.49-54
NLP, NC
(Joint)
2020-01-25
16:25
Okinawa Miyakojima Marine Terminal Reinforcement learning of communication strategy between players of the game of Contract Bridge
Yotaro Yamaguchi, Sotetsu Koyamada, Ken Nakae, Shin Ishii (Kyoto Univ.) NLP2019-111
Contract bridge (bridge) is a card game in which four players are divided into two teams and cooperate with a partner to... [more] NLP2019-111
pp.131-134
NC, IBISML, IPSJ-MPS, IPSJ-BIO [detail] 2019-06-18
13:30
Okinawa Okinawa Institute of Science and Technology Hybrid Reinforcement and Imitation Learning for Human-Like Agents
Rousslan Fernand Julien Dossa, Xinyu Lian (Kobe Uni), Hirokazu Nomoto (EQUOS RESEARCH), Takashi Matsubara, Kuniaki Uehara (Kobe Uni) NC2019-16 IBISML2019-14
Reinforcement learning methods achieve performance superior to humans in a wide range of complex tasks and uncertain env... [more] NC2019-16 IBISML2019-14
pp.69-74(NC), pp.91-96(IBISML)
IN 2018-01-23
14:25
Aichi WINC AICHI Community Extraction Using Online Battle Data for Game AIs Capable to Infer Imperfect Information
Ryohei Watanabe, Komei Arasawa, Shun Hattori (Muroran Inst. of Tech.) IN2017-87
In these days, playing video games competitively, called “e-sports,” is getting in fashion. But most of video games are ... [more] IN2017-87
pp.91-96
 Results 1 - 6 of 6  /   
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