Tomohiro Yamaguchi

Tomohiro Yamaguchi received his M.E. degree from Osaka University, Japan, in 1987. He joined Mitsubishi Electric Corporation in 1987 and moved to Matsushita Electric Industrial in 1988. He worked at Osaka University from 1991 to 1998 as a research associate and got Doctor of Engineering Degree from Osaka University in 1996. He moved to Nara National College of Technology as associate professor in 1998 and is currently a professor from 2007. His research interests include interactive recommender system, music information retrieval, multiagent reinforcement learning, autonomous learning agent, human-agent interaction, learning support system, human learning process and mastery process. He is a member of The Japanese Society for Artificial Intelligence and The Society of Instrument and Control Engineers, Japan.

Publications

The Explainable Model to Multi-Objective Reinforcement Learning Toward an Autonomous Smart System
The Explainable Model to Multi-Objective Reinforcement Learning Toward an Autonomous Smart System
Tomohiro Yamaguchi. © 2023. 17 pages.
The mission of this chapter is to add an explainable model to multi-goal reinforcement learning toward an autonomous smart system to design both complex behaviors and complex...
Formalizing Model-Based Multi-Objective Reinforcement Learning With a Reward Occurrence Probability Vector
Formalizing Model-Based Multi-Objective Reinforcement Learning With a Reward Occurrence Probability Vector
Tomohiro Yamaguchi, Yuto Kawabuchi, Shota Takahashi, Yoshihiro Ichikawa, Keiki Takadama. © 2022. 32 pages.
The mission of this chapter is to formalize multi-objective reinforcement learning (MORL) problems where there are multiple conflicting objectives with unknown weights. The...
Model-Based Multi-Objective Reinforcement Learning by a Reward Occurrence Probability Vector
Model-Based Multi-Objective Reinforcement Learning by a Reward Occurrence Probability Vector
Tomohiro Yamaguchi, Shota Nagahama, Yoshihiro Ichikawa, Yoshimichi Honma, Keiki Takadama. © 2020. 27 pages.
This chapter describes solving multi-objective reinforcement learning (MORL) problems where there are multiple conflicting objectives with unknown weights. Previous model-free...
Awareness-Based Recommendation by Passively Interactive Learning: Toward a Probabilistic Event
Awareness-Based Recommendation by Passively Interactive Learning: Toward a Probabilistic Event
Tomohiro Yamaguchi, Takuma Nishimura, Shota Nagahama, Keiki Takadama. © 2019. 29 pages.
In artificial intelligence and robotics, one of the important issues is to design human interface. There are two issues: One is the machine-centered interaction design. Another...
Awareness Based Recommendation: Passively Interactive Learning System
Awareness Based Recommendation: Passively Interactive Learning System
Tomohiro Yamaguchi, Takuma Nishimura, Keiki Takadama. © 2019. 20 pages.
In Artificial Intelligence and Robotics, one of the important issues is to design Human interface. There are two issues, one is the machine-centered interaction design to adapt...
Awareness-Based Recommendation Toward a New Preference: Evaluation of the Awareness Effect
Awareness-Based Recommendation Toward a New Preference: Evaluation of the Awareness Effect
Tomohiro Yamaguchi, Takuma Nishimura, Keiki Takadama. © 2019. 22 pages.
In mechatronics and robotics, one of the important issues is to design human interface. There are two issues on interaction design research. One is the way to education and...
Analyzing the Goal-Finding Process of Human Learning With the Reflection Subtask
Analyzing the Goal-Finding Process of Human Learning With the Reflection Subtask
Tomohiro Yamaguchi, Yuki Tamai, Keiki Takadama. © 2018. 18 pages.
This chapter reports the authors' experimental results on analyzing the human goal-finding process in continuous learning. The objective of this research is to make clear the...
Designing the Learning Goal Space for Human Toward Acquiring a Creative Learning Skill
Designing the Learning Goal Space for Human Toward Acquiring a Creative Learning Skill
Takato Okudo, Tomohiro Yamaguchi, Keiki Takadama. © 2018. 16 pages.
This chapter presents the way to design a learning support system toward acquiring a creative skill on learning. There are two research goals. One is to establish designing the...
Awareness-Based Recommendation toward a New Preference: Evaluation of the Awareness Effect
Awareness-Based Recommendation toward a New Preference: Evaluation of the Awareness Effect
Tomohiro Yamaguchi, Takuma Nishimura, Keiki Takadama. © 2015. 23 pages.
In mechatronics and robotics, one of the important issues is to design human interface. There are two issues on interaction design research. One is the way to education and...
Awareness-Based Recommendation: Toward the Human Adaptive and Friendly Interactive Learning System
Awareness-Based Recommendation: Toward the Human Adaptive and Friendly Interactive Learning System
Tomohiro Yamaguchi, Takuma Nishimura, Keiki Takadama. © 2013. 15 pages.
This chapter describes the interactive learning system to assist positive change in the preference of a human toward the true preference. First, an introduction to interactive...