Kazuteru Miyazaki

Publication Activity (10 Years)

Years Active: 1997-2024
Publications (10 Years): 22

Top Topics

Reinforcement Learning

Eligibility Traces

Top Venues

J. Adv. Comput. Intell. Intell. Informatics

Cogn. Syst. Res.

Publications

Kazuteru Miyazaki, Shu Yamaguchi, Rie Mori, Yumiko Yoshikawa, Takanori Saito, Toshiya Suzuki
Proposal of a Course-Classification Support System Using Deep Learning and its Evaluation When Combined with Reinforcement Learning. J. Adv. Comput. Intell. Intell. Informatics 28 (2) (2024)
Kazuteru Miyazaki, Hitomi Miyazaki
Suppression of negative tweets using reinforcement learning systems. Cogn. Syst. Res. 84 (2024)
Kazuteru Miyazaki, Masaaki Ida
Performance evaluation of character-level CNNs using tweet data and analysis for weight perturbations. Artif. Life Robotics 29 (2) (2024)
Kazuteru Miyazaki, Keiki Takadama
Editorial: Cutting Edge of Reinforcement Learning and its Hybrid Methods. J. Adv. Comput. Intell. Intell. Informatics 28 (2) (2024)
Naoki Kodama, Taku Harada, Kazuteru Miyazaki
Traffic Signal Control System Using Deep Reinforcement Learning With Emphasis on Reinforcing Successful Experiences. IEEE Access 10 (2022)
Kazuteru Miyazaki
Modeling of placebo effect in stochastic reward tasks by reinforcement learning. BICA*AI (2022)
Naoki Kodama, Taku Harada, Kazuteru Miyazaki
Home Energy Management Algorithm Based on Deep Reinforcement Learning Using Multistep Prediction. IEEE Access 9 (2021)
Kazuteru Miyazaki
Proposal and evaluation of deep exploitation-oriented learning under multiple reward environment. Cogn. Syst. Res. 70 (2021)
Kazuteru Miyazaki
Application of Deep Reinforcement Learning to Decision-Making System based on Consciousness. BICA (2020)
Kazuteru Miyazaki
Classification of Medical Data using Character-level CNN. ICISS (2020)
Naoki Kodama, Taku Harada, Kazuteru Miyazaki
Deep Reinforcement Learning with Dual Targeting Algorithm. IJCNN (2019)
Kazuteru Miyazaki, Masaaki Ida
Consistency Assessment between Diploma Policy and Curriculum Policy using Character-Level CNN. SCIS&ISIS (2018)
Kazuteru Miyazaki, Naoki Kodama, Hiroaki Kobayashi
Proposal and Evaluation of an Indirect Reward Assignment Method for Reinforcement Learning by Profit Sharing Method. IntelliSys (1) (2018)
Daisuke Shiraishi, Kazuteru Miyazaki, Hiroaki Kobayashi
Proposal of Detour Path Suppression Method in PS Reinforcement Learning and Its Application to Altruistic Multi-agent Environment. PRIMA (2018)
Naoki Kodama, Kazuteru Miyazaki, Taku Harada
A Proposal for Reducing the Number of Trial-and-Error Searches for Deep Q-Networks Combined with Exploitation-Oriented Learning. ICMLA (2018)
Kazuteru Miyazaki
Proposal of a Deep Q-network with Profit Sharing. BICA (2017)
Kazuteru Miyazaki
Exploitation-Oriented Learning with Deep Learning - Introducing Profit Sharing to a Deep Q-Network -. J. Adv. Comput. Intell. Intell. Informatics 21 (5) (2017)
Keiki Takadama, Kazuteru Miyazaki
Editorial: Cutting Edge of Reinforcement Learning and its Hybrid Methods. J. Adv. Comput. Intell. Intell. Informatics 21 (5) (2017)
Kazuteru Miyazaki, Koudai Furukawa, Hiroaki Kobayashi
Proposal of PSwithEFP and its Evaluation in Multi-Agent Reinforcement Learning. J. Adv. Comput. Intell. Intell. Informatics 21 (5) (2017)
Kazuteru Miyazaki
A Study of an Indirect Reward on Multi-agent Environments. BICA (2016)
Kazuteru Miyazaki, Koudai Furukawa, Hiroaki Kobayashi
Proposal and Evaluation of an Action Selection Strategy with Expected Failure Probability in Multi-agent Learning. ICA (2016)
Kazuteru Miyazaki, Koudai Furukawa, Hiroaki Kobayashi
Proposal of an Action Selection Strategy with Expected Failure Probability and Its Evaluation in Multi-agent Reinforcement Learning. EUMAS/AT (2016)
Kazuteru Miyazaki, Jun'ichi Takeno
The Necessity of a Secondary System in Machine Consciousness. BICA (2014)
Kazuteru Miyazaki
Proposal of an Exploitation-oriented Learning Method on Multiple Rewards and Penalties Environments and the Design Guideline. J. Comput. 8 (7) (2013)
Kazuteru Miyazaki, Masaki Itou, Hiroaki Kobayashi
Evaluation of the Improved Penalty Avoiding Rational Policy Making Algorithm in Real World Environment. ACIIDS (1) (2012)
Seiya Kuroda, Kazuteru Miyazaki, Hiroaki Kobayashi
Introduction of Fixed Mode States into Online Reinforcement Learning with Penalties and Rewards and its Application to Biped Robot Waist Trajectory Generation. J. Adv. Comput. Intell. Intell. Informatics 16 (6) (2012)
Kazuteru Miyazaki, Masaaki Ida
Proposal of an Active Course Classification Support system with Exploitation-oriented Learning extended by positive and negative examples. SCIS&ISIS (2012)
Kazuteru Miyazaki
Proposal of the Continuous-Valued Penalty Avoiding Rational Policy Making Algorithm. J. Adv. Comput. Intell. Intell. Informatics 16 (2) (2012)
Kazuteru Miyazaki, Masaaki Ida
Proposal and Evaluation of the Active Course Classification Support System with Exploitation-Oriented Learning. EWRL (2011)
Seiya Kuroda, Kazuteru Miyazaki, Hiroaki Kobayashi
Introduction of Fixed Mode States into Online Profit Sharing and Its Application to Waist Trajectory Generation of Biped Robot. EWRL (2011)
Kazuteru Miyazaki
The Penalty Avoiding Rational Policy Making Algorithm in Continuous Action Spaces. IDEAL (2010)
Takuji Watanabe, Kazuteru Miyazaki, Hiroaki Kobayashi
A New Improved Penalty Avoiding Rational Policy Making Algorithm for Keepaway with Continuous State Spaces. J. Adv. Comput. Intell. Intell. Informatics 13 (6) (2009)
Kazuteru Miyazaki, Shigenobu Kobayashi
Exploitation-Oriented Learning PS-r#. J. Adv. Comput. Intell. Intell. Informatics 13 (6) (2009)
Kazuteru Miyazaki, Shigenobu Kobayashi
Proposal of Exploitation-Oriented Learning PS-r#. IDEAL (2008)
Kazuteru Miyazaki, Shigenobu Kobayashi
Reinforcement Learning for Penalty Avoidance in Continuous State Spaces. J. Adv. Comput. Intell. Intell. Informatics 11 (6) (2007)
Daisuke Katagami, Katsumi Nitta, Kazuteru Miyazaki
Multi User Learning Agent on the Distribution of MDPs. RO-MAN (2006)
Kazuteru Miyazaki, Sougo Tsuboi, Shigenobu Kobayashi
Development of a reinforcement learning system to play Othello. Artif. Life Robotics 7 (4) (2004)
Kazuteru Miyazaki, Shigenobu Kobayashi
Rationality of Reward Sharing in Multi-agent Reinforcement Learning. New Gener. Comput. 19 (2) (2001)
Kazuteru Miyazaki, Shigenobu Kobayashi
Reinforcement learning for penalty avoiding policy making. SMC (2000)
Sachiyo Arai, Kazuteru Miyazaki, Shigenobu Kobayashi
Multi-agent Reinforcement Learning for Crane Control Problem: Designing Rewards for Conflict Resolution. ISADS (1999)
Kazuteru Miyazaki, Shigenobu Kobayashi
Rationality of Reward Sharing in Multi-agent Reinforcement Learning. PRIMA (1999)
Kazuteru Miyazaki, Masayuki Yamamura, Shigenobu Kobayashi
k-Certainty Exploration Method: An Action Selector to Identify the Environment in Reinforcement Learning. Artif. Intell. 91 (1) (1997)
Hajime Kimura, Kazuteru Miyazaki, Shigenobu Kobayashi
Reinforcement Learning in POMDPs with Function Approximation. ICML (1997)