Shinji Ito (Ph.D.)
Title
Team Leader
Members
-
Team leaderShinji Ito
-
Visiting scientistJunya Honda
-
Visiting scientistTaira Tsuchiya
-
Visiting scientistJunpei Komiyama
-
Visiting scientistKazushi Tsutsui
-
Visiting scientistShinsaku Sakaue
-
Visiting scientistTasuku Soma
-
Student traineeManh Quan Nguyen
-
Student traineeCanzhe Zhao
Introduction
The sequential decision-making team works to develop algorithms and theories for making rational decisions in a sequential manner in the face of forecast uncertainty and environmental fluctuations. In recent years, along with the evolution of information technology, there has been a demand for technology to make rational decisions based on the large amount of data being generated in real-time in today's world. To meet this challenge, we promote research related to online learning, bandit problems, and reinforcement learning, aiming to understand effective decision-making algorithms in a fluctuating environment and to construct and extend theoretical systems that support such algorithms.
Main Research Field
Informatics
Research Field
Theory of informatics / Mathematical informatics / Intelligent informatics
Research Subjects
Sequential decision-making
Online learning
Bandit problems
Reinforcement learning
Learning theory
Online learning
Bandit problems
Reinforcement learning
Learning theory
Poster(s)
- FY2023 Research Results(PDF 3MB) (Japanese version)
Related posts
posted on October 2, 2024 17:33Information
posted on May 15, 2024 17:34Information
posted on May 9, 2024 22:55Information
posted on April 30, 2024 18:24Information
posted on December 15, 2023 10:39Information
