Kazuteru Miyazaki

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Proposal and Evaluation of Reward Sharing Method Based on Safety Level

Kazuteru Miyazaki, Naoki Kodama, Hiroaki Kobayashi, 2018 .

Consideration on Document Structure of Syllabi:- Advanced Engineering Programs of Colleges of Technology -

Kazuteru Miyazaki, Masaaki Ida, 2008 .

Introduction of Fixed Mode States into Online Profit Sharing and Its Application to Waist Trajectory Generation of Biped Robot

Kazuteru Miyazaki, Hiroaki Kobayashi, Seiya Kuroda, 2011, EWRL.

A course classification suport system using syllabus data

Hajime Kita, Kazuteru Miyazaki, Takayuki Nozawa, 2004 .

The Necessity of a Secondary System in Machine Consciousness

Kazuteru Miyazaki, Jun'ichi Takeno, K. Miyazaki, 2014, BICA.

Proposal of an Active Course Classification Support system with Exploitation-oriented Learning extended by positive and negative examples

Kazuteru Miyazaki, Masaaki Ida, 2012, The 6th International Conference on Soft Computing and Intelligent Systems, and The 13th International Symposium on Advanced Intelligence Systems.

Development of a reinforcement learning system to play Othello

Shigenobu Kobayashi, Kazuteru Miyazaki, Sougo Tsuboi, 2006, Artificial Life and Robotics.

Reinforcement learning for penalty avoiding policy making

Shigenobu Kobayashi, Kazuteru Miyazaki, Shigenobu Kobayashi, 2000, Smc 2000 conference proceedings. 2000 ieee international conference on systems, man and cybernetics. 'cybernetics evolving to systems, humans, organizations, and their complex interactions' (cat. no.0.

Reinforcement Learning for Crawling on a Robot Arm

Shigenobu Kobayashi, Kazuteru Miyazaki, Hajime Kimura, 1997 .

Construction of Consistency Judgment System of Diploma Policy and Curriculum Policy using Character-level CNN

Kazuteru Miyazaki, Masaaki Ida, 2019 .

Proposal of an Exploitation-oriented Learning Method on Multiple Rewards and Penalties Environments and the Design Guideline

Kazuteru Miyazaki, 2013, J. Comput..

Proposed Decision-Making System Based on Consciousness in Multiple Rewards and Penalties Environments

Kazuteru Miyazaki, K. Miyazaki, 2015 .

Development of the active course classification support system with a learning mechanism

Kazuteru Miyazaki, Masaaki Ida, Fuyuki Yoshikane, 2009, 2009 ICCAS-SICE.

Construction of consistency judgment system of diploma policy and curriculum policy using character‐level CNN

Kazuteru Miyazaki, Masaaki Ida, K. Miyazaki, 2019 .

Reinforcement Learning for Penalty Avoiding Rational Policy Making

Shigenobu Kobayashi, Kazuteru Miyazaki, Sougo Tsuboi, 2001 .

Reinforcement Learning Systems under Discrete Markov Decision Processes

Kazuteru Miyazaki, 1997 .

Rationality of Reward Sharing in Multi-agent Reinforcement Learning

Shigenobu Kobayashi, Kazuteru Miyazaki, Shigenobu Kobayashi, 1999, PRIMA.

Application of Document Analysis － Syllabus Classification for Degree Awarding －

Kazuteru Miyazaki, Masaaki Ida, 2014 .

Proposal of the Active Course Classification Support System to support the Classification of Courses at the Degree-Awarding of NIAD-UE

Hajime Kita, Kazuteru Miyazaki, Takayuki Nozawa, 2005 .

The Penalty Avoiding Rational Policy Making Algorithm in Continuous Action Spaces

Kazuteru Miyazaki, 2010, IDEAL.

Reinforcement Learning for Penalty Avoidance in Continuous State Spaces

Shigenobu Kobayashi, Kazuteru Miyazaki, Shigenobu Kobayashi, 2007, J. Adv. Comput. Intell. Intell. Informatics.

Generating Cooperative Behavior by Multi-Agent Profit Sharing on the Soccer Game

Kazuteru Miyazaki, Hiroaki Kobayashi, Takashi Terada, 2003 .

Editorial: Cutting Edge of Reinforcement Learning and its Hybrid Methods

Kazuteru Miyazaki, Keiki Takadama, K. Miyazaki, 2017, J. Adv. Comput. Intell. Intell. Informatics.

Proposal of reward sharing method based on safety level and verification of its effectiveness in multi-agent environment

Kazuteru Miyazaki, Naoki Kodama, Hiroaki Kobayshi, 2017, 2017 56th Annual Conference of the Society of Instrument and Control Engineers of Japan (SICE).

Proposal and Evaluation of the Active Course Classification Support System for Degree Awarding : Control of the Number of Candidate Courses in Classification

Hajime Kita, Kazuteru Miyazaki, Takayuki Nozawa, 2005 .

Exploitation-Oriented Learning XoL: A New Approach to Machine Learning Based on Trial-and-Error Searches

Kazuteru Miyazaki, K. Miyazaki, 2011 .

A New Improved Penalty Avoiding Rational Policy Making Algorithm for Keepaway with Continuous State Spaces

Kazuteru Miyazaki, Hiroaki Kobayashi, Takuji Watanabe, 2009, J. Adv. Comput. Intell. Intell. Informatics.

N-029 Development of Syllabus Database and its Application

Kazuteru Miyazaki, Takayuki Nozawa, Hajime Kita, 2004 .

Threshold learning in the improved penalty avoiding rational policy making algorithm

Kazuteru Miyazaki, Hiroaki Kobayashi, Ryouhei Kobayashi, 2010, Proceedings of SICE Annual Conference 2010.

Proposal of Detour Path Suppression Method in PS Reinforcement Learning and Its Application to Altruistic Multi-agent Environment

Daisuke Shiraishi, Kazuteru Miyazaki, Hiroaki Kobayashi, 2018, PRIMA.

Special Issue on New Trends in Reinforcement Learning

Kazuteru Miyazaki, Keiki Takadama, 2009 .

A Survey on Learning for Agents ( "Foundations and Applications of Agents")

Shigenobu Kobayashi, Kazuteru Miyazaki, Masayuki Yamamura, 1995 .

Proposal of the Continuous-Valued Penalty Avoiding Rational Policy Making Algorithm

Kazuteru Miyazaki, K. Miyazaki, 2012, J. Adv. Comput. Intell. Intell. Informatics.

Reinforcement Learning in POMDPs with Function Approximation

Shigenobu Kobayashi, Kazuteru Miyazaki, Hajime Kimura, 1997, ICML.

Controlling Multiple Cranes Using Multi-Agent Reinforcement Learning: Emerging Coordination among Competitive Agents

Sachiyo Arai, Shigenobu Kobayashi, Kazuteru Miyazaki, 2000 .

An extension of the rational policy making algorithm to continuous state spaces

Shigenobu Kobayashi, Kazuteru Miyazaki, Hajime Kimura, 2007 .

Exploitation-Oriented Learning with Deep Learning - Introducing Profit Sharing to a Deep Q-Network -

Kazuteru Miyazaki, 2017, J. Adv. Comput. Intell. Intell. Informatics.

Proposal of Exploitation-Oriented Learning PS-r#

Shigenobu Kobayashi, Kazuteru Miyazaki, 2008, IDEAL.

Multi User Learning Agent on the Distribution of MDPs

Kazuteru Miyazaki, Katsumi Nitta, Daisuke Katagami, 2006, ROMAN 2006 - The 15th IEEE International Symposium on Robot and Human Interactive Communication.

Analyzing Robustness in Estimated-based Profit Sharing : A Theory of condition to suppress any ineffective rules and its approach to local minimum

Kazuteru Miyazaki, Keiki Takadama, Tsuyoshi Nehashi, 2007 .

On Stable Profit Sharing Reinforcement Learning with Expected Failure Probability

Kazuteru Miyazaki, Daisuke Mizuno, Hiroaki Kobayashi, 2018, BICA 2018.

Proposal of a Deep Q-network with Profit Sharing

Kazuteru Miyazaki, 2018 .

Automatic tuning of judgement parameter in continuous state exploitation-oriented learning

Kazuteru Miyazaki, 2010, Proceedings of SICE Annual Conference 2010.

Proposal and Evaluation of an Action Selection Strategy with Expected Failure Probability in Multi-agent Learning

Kazuteru Miyazaki, Hiroaki Kobayashi, Koudai Furukawa, 2016, 2016 IEEE International Conference on Agents (ICA).

Distributed deep reinforcement learning method using profit sharing for learning acceleration

Kazuteru Miyazaki, Taku Harada, Naoki Kodama, 2020 .

Profit Sharing Based Reinforcement Learning Systems in Continuous State Spaces

Shigenobu Kobayashi, Kazuteru Miyazaki, 2006 .

Consideration on Document Structure of Syllabi

Kazuteru Miyazaki, Masaaki Ida, 2008 .

A Study of an Indirect Reward on Multi-agent Environments

Kazuteru Miyazaki, K. Miyazaki, 2016, BICA.

Syllabus Database System and its Application to Comparative Analysis of Curricula

Hajime Kita, Kazuteru Miyazaki, Takayuki Nozawa, 2005 .

Introduction of Fixed Mode States into Online Reinforcement Learning with Penalties and Rewards and its Application to Biped Robot Waist Trajectory Generation

Kazuteru Miyazaki, Hiroaki Kobayashi, Seiya Kuroda, 2012, J. Adv. Comput. Intell. Intell. Informatics.

Classification of Medical Data using Character-level CNN

Kazuteru Miyazaki, K. Miyazaki, 2020, ICISS.

Proposal of an Action Selection Strategy with Expected Failure Probability and Its Evaluation in Multi-agent Reinforcement Learning

Kazuteru Miyazaki, Hiroaki Kobayashi, Koudai Furukawa, 2016, EUMAS/AT.

A Proposal for Reducing the Number of Trial-and-Error Searches for Deep Q-Networks Combined with Exploitation-Oriented Learning

Kazuteru Miyazaki, Taku Harada, Naoki Kodama, 2018, 2018 17th IEEE International Conference on Machine Learning and Applications (ICMLA).

Evaluation of the Improved Penalty Avoiding Rational Policy Making Algorithm in Real World Environment

Kazuteru Miyazaki, Hiroaki Kobayashi, Masaki Itou, 2012, ACIIDS.

An Extension of Profit Sharing to Partially Observable Markov Decision Processes: Proposition of PS-r* and its Evaluation

Shigenobu Kobayashi, Kazuteru Miyazaki, 2003 .

Consistency Assessment between Diploma Policy and Curriculum Policy using Character-Level CNN

Kazuteru Miyazaki, Masaaki Ida, 2018, 2018 Joint 10th International Conference on Soft Computing and Intelligent Systems (SCIS) and 19th International Symposium on Advanced Intelligent Systems (ISIS).

Proposal of PSwithEFP and its Evaluation in Multi-Agent Reinforcement Learning

Kazuteru Miyazaki, Hiroaki Kobayashi, Koudai Furukawa, 2017, J. Adv. Comput. Intell. Intell. Informatics.

Multi-agent reinforcement learning for crane control problem: designing rewards for conflict resolution

Sachiyo Arai, Shigenobu Kobayashi, Kazuteru Miyazaki, 1999, Proceedings. Fourth International Symposium on Autonomous Decentralized Systems. - Integration of Heterogeneous Systems -.

Proposal and Evaluation of an Indirect Reward Assignment Method for Reinforcement Learning by Profit Sharing Method

Kazuteru Miyazaki, Hiroaki Kobayashi, Naoki Kodama, 2018, IntelliSys.

Rationality of reward sharing in multi-agent reinforcement learning

Shigenobu Kobayashi, Kazuteru Miyazaki, K. Miyazaki, 1999, New Generation Computing.

Exploitation-Oriented Learning PS-r#

Shigenobu Kobayashi, Kazuteru Miyazaki, K. Miyazaki, 2009, J. Adv. Comput. Intell. Intell. Informatics.

Research on Consistency between Diploma Policies and Nomenclature of Major Disciplines: Deep Learning Approach

Kazuteru Miyazaki, Nozomi Takahashi, Rie Mori, 2019, ICIET 2019.

Deep Reinforcement Learning with Dual Targeting Algorithm

Kazuteru Miyazaki, Taku Harada, Naoki Kodama, 2019, 2019 International Joint Conference on Neural Networks (IJCNN).

Syllabus Retrieval Considering Relationships between the Search Term and its Synonyms

Hajime Kita, Kazuteru Miyazaki, Takayuki Nozawa, 2006 .

Proposal of a propagation algorithm of the Expected Failure Probability and the effectiveness on multi-agent environments

Kazuteru Miyazaki, Hiroaki Kobayashi, Hiroki Muraoka, 2013, The SICE Annual Conference 2013.

A study on the practical use of course classification support system in degree-awarding of NIAD-UE

Kazuteru Miyazaki, Masaaki Ida, K. Miyazaki, 2014, 2014 Proceedings of the SICE Annual Conference (SICE).

k-Certainty Exploration Method: An Action Selector to Identify the Environment in Reinforcement Learning

Shigenobu Kobayashi, Kazuteru Miyazaki, Masayuki Yamamura, 1997, Artif. Intell..

Proposal and Evaluation of the Active Course Classification Support System with Exploitation-Oriented Learning

Kazuteru Miyazaki, Masaaki Ida, K. Miyazaki, 2011, EWRL.

Home Energy Management Algorithm Based on Deep Reinforcement Learning Using Multistep Prediction

Kazuteru Miyazaki, Taku Harada, Naoki Kodama, 2021, IEEE Access.

Proposal and evaluation of deep exploitation-oriented learning under multiple reward environment

Kazuteru Miyazaki, 2021, Cognitive Systems Research.