Kunikazu Kobayashi

发表

Designing Wavelet Networks Using Geneti Algorithms Designing Wavelet Networks Using Geneti Algorithms

Kunikazu Kobayashi, 1997 .

Reinforcement Learning Using Adaptive Search Method

Kunikazu Kobayashi, Kosuke Umesako, M. Obayashi, 2002 .

Investigating the influence of PFC transection and nicotine on dynamics of AMPA and NMDA receptors of VTA dopaminergic neurons

Ting Y. Chen, M. Akay, Andrei Dragomir, 2011, Journal of NeuroEngineering and Rehabilitation.

Self-Organized Fuzzy Reinforcement Learning System

Kunikazu Kobayashi, Masanao Obayashi, Kosuke Umesako, 2003 .

A Swarm Learning System using Self-Organizing Fuzzy Neural Network and Reinforcement Learning

Kunikazu Kobayashi, M. Obayashi, T. Kuremoto, 2017 .

Food Volume Estimation Using 3D Shape Approximation for Medication Management Support

Kunikazu Kobayashi, Takuo Suzuki, Kana Futatsuishi, 2018 .

ELMAN TYPE RECURRENT NEURAL NETWORK WITH PARAMETRIC BIAS AND ITS APPLICATION TO MULTI-ACTION LEARNING OF ROBOT

Kunikazu Kobayashi, Takashi Kuremoto, Keita Morisaki, 2015 .

Cooperative Action Acquisition Based on Intention Estimation in a Multi-Agent Reinforcement Learning System

Kunikazu Kobayashi, Tatsuya Tsubakimoto, Kunikazu Kobayashi, 2017 .

A New Method for Faster Neural Networks Learning Introducing Functions of Synaptic Weights and Its Application to Nonlinear System Control

Kunikazu Kobayashi, Masanao Obayashi, Kousuke Umesako, 2001 .

A Wavelet Neural Network with Evolutionally Generated Structure

Kunikazu Kobayashi, Toyoshi Torioka, Nobuaki Ueda, 1997 .

Reinforcement Learning System with Time Varying Parameters Using Neural Networks

Hiroaki Kitano, Kunikazu Kobayashi, Masanao Obayashi, 2004 .

Indirect Adaptive Self-structuring Fuzzy Neural Network Control System

Kunikazu Kobayashi, Masanao Obayashi, Takashi Kuremoto, 2010 .

A Control System Based on Auto-Fusion Cerebellar Perceptron Improved Model and Its Application to Consensus Problem

Shingo Mabu, Kunikazu Kobayashi, Masanao Obayashi, 2014 .

A method for analyzing the spatiotemporal changes of chaotic neural networks

Kunikazu Kobayashi, M. Obayashi, T. Kuremoto, 2013, Artificial Life and Robotics.

The effect of the internal parameters on association performance of a chaotic neural network

Kunikazu Kobayashi, T. Kuremoto, Shun Watanabe, 2022 .

Fundamental consideration on self-formation of recognition cells

Kunikazu Kobayashi, Toyoshi Torioka, Nobuhiko Ikeda, 1994, Neural Networks.

Evolutionary reinforcement learning system with time‐varying parameters

Kunikazu Kobayashi, Masanao Obayashi, Kosuke Umesako, 2006 .

A Reinforcement Learning System Based on State Space Construction Using Fuzzy ART A Reinforcement Learning System Based on State Space Construction Using Fuzzy ART

Kunikazu Kobayashi, Masanao Obayashi, Takashi Kuremoto, 2005 .

Evolutionary Reinforcement Learning System with Time-Varying Parameters

Kunikazu Kobayashi, Masanao Obayashi, Kosuke Umesako, 2004 .

An Improved Internal Model for Swarm Formation and Adaptive Swarm Behavior Acquisition

Kunikazu Kobayashi, Masanao Obayashi, Takashi Kuremoto, 2009, J. Circuits Syst. Comput..

Adaptive swarm behavior acquisition by a neuro-fuzzy system and reinforcement learning algorithm

Kunikazu Kobayashi, Masanao Obayashi, Takashi Kuremoto, 2009, Int. J. Intell. Comput. Cybern..

Improvement of Robot's Self-localization by Using Observer View Positional Information

Kunikazu Kobayashi, Yo Aizawa, Takuo Suzuki, 2017 .

Training Deep Neural Networks with Reinforcement Learning for Time Series Forecasting

Shingo Mabu, Kunikazu Kobayashi, Masanao Obayashi, 2019, Time Series Analysis - Data, Methods, and Applications.

The Recollection Characteristics of Generalized MCNN Using Different Control Methods

Shingo Mabu, Shun Watanabe, Kunikazu Kobayashi, 2014, J. Robotics Netw. Artif. Life.

The recollection characteristics of a generalized MCNN

Shingo Mabu, Kunikazu Kobayashi, Masanao Obayashi, 2013, The SICE Annual Conference 2013.

Handwriting character classification using Freeman’s olfactory KIII model

Kunikazu Kobayashi, Masanao Obayashi, Takashi Kuremoto, 2012, Artificial Life and Robotics.

Dynamical recollection of interconnected neural networks using meta‐heuristics

Shun Watanabe, Kunikazu Kobayashi, Masanao Obayashi, 2012 .

The Dynamical Recollection of Interconnected Neural Networks Using Meta-heuristics

Shun Watanabe, Kunikazu Kobayashi, Masanao Obayashi, 2011 .

Intelligent agent construction using the attentive characteristic patterns of chaotic neural networks

Kunikazu Kobayashi, Masanao Obayashi, Takashi Kuremoto, 2010, Artificial Life and Robotics.

A dynamic associative memory system by adopting an amygdala model

Kunikazu Kobayashi, Masanao Obayashi, Takashi Kuremoto, 2009, Artificial Life and Robotics.

Shapes of nonmonotonic activation functions in a chaotic neural network associative memory model and its evaluation

Kunikazu Kobayashi, Masanao Obayashi, Takashi Kuremoto, 2008 .

A Hippocampus-Neocortex Model for Chaotic Association

Kunikazu Kobayashi, Masanao Obayashi, Takashi Kuremoto, 2007, Trends in Neural Computation.

Shapes of Non-monotonous Activation Functions in Chaotic Neural Network Associative Memory Model and Its Evaluation

Kunikazu Kobayashi, Masanao Obayashi, Takashi Kuremoto, 2006 .

A Chaotic Model of Hippocampus-Neocortex

Kunikazu Kobayashi, Masanao Obayashi, Takashi Kuremoto, 2005, ICNC.

A chaotic memory search model based on associative dynamics using features in stored patterns

Kunikazu Kobayashi, Masanao Obayashi, K. Watanabe, 2002, Proceedings of the 41st SICE Annual Conference. SICE 2002..

An Improved Internal Model of Autonomous Robots by a Psychological Approach

Kunikazu Kobayashi, Masanao Obayashi, Takashi Kuremoto, 2011, Cognitive Computation.

Forecast chaotic time series data by DBNs

Shingo Mabu, Kunikazu Kobayashi, Masanao Obayashi, 2014, 2014 7th International Congress on Image and Signal Processing.

Time series forecasting using a deep belief network with restricted Boltzmann machines

Kunikazu Kobayashi, Masanao Obayashi, Takashi Kuremoto, 2014, Neurocomputing.

Forecasting Real Time Series Data using Deep Belief Net and Reinforcement Learning

Shingo Mabu, Kunikazu Kobayashi, Masanao Obayashi, 2017, J. Robotics Netw. Artif. Life.

A Neuro-fuzzy Learning System for Adaptive Swarm Behaviors Dealing with Continuous State Space

Kunikazu Kobayashi, Masanao Obayashi, Takashi Kuremoto, 2008, ICIC.

Time Series Prediction Using DBN and ARIMA

Shingo Mabu, Kunikazu Kobayashi, Masanao Obayashi, 2015, 2015 International Conference on Computer Application Technologies.

A Robust Reinforcement Learning System Using Concept of Sliding Mode Control for Unknown Nonlinear Dynamical System

Kunikazu Kobayashi, Masanao Obayashi, Takashi Kuremoto, 2011 .

A robust reinforcement learning using the concept of sliding mode control

M. Obayashi, N. Nakahara, T. Kuremoto, 2009, Artificial Life and Robotics.

A Self-Organized Fuzzy-Neuro Reinforcement Learning System for Continuous State Space for Autonomous Robots

Kunikazu Kobayashi, Masanao Obayashi, Takashi Kuremoto, 2008, 2008 International Conference on Computational Intelligence for Modelling Control & Automation.

A Real-time Reinforcement Learning Control System with H^|^infin; Tracking Performance Compensator

Kunikazu Kobayashi, Masanao Obayashi, Shogo Uchiyama, 2012 .

A Robust Reinforcement Learning Control Design Method for Nonlinear System with Partially Unknown Structure

Kunikazu Kobayashi, Kazuhiro Nakano, Masanao Obayashi, 2010 .

A Novel Approach to Time Series Forecasting using Deep Learning and Linear Model

Shingo Mabu, Kunikazu Kobayashi, Masanao Obayashi, 2016 .

Construction and Application of Learning Petri Net

Kunikazu Kobayashi, Masanao Obayashi, Takashi Kuremoto, 2012 .

Designing Wavelet Networks Using Geneti Algorithms Designing Wavelet Networks Using Geneti Algorithms

Kunikazu Kobayashi, 1997 .

A WAVELET NEURAL NETWORK FOR FUNCTION APPROXIMATION AND NETWORK OPTIMIZATION

Kunikazu Kobayashi, Toyoshi Torioka, Kunikazu Kobayashi, 1994 .

Food Volume Estimation Using 3D Shape Approximation for Medication Management Support

Kunikazu Kobayashi, Takuo Suzuki, Kana Futatsuishi, 2018, 2018 3rd Asia-Pacific Conference on Intelligent Robot Systems (ACIRS).

An Improved Reinforcement Learning System Using Affective Factors

Shingo Mabu, Kunikazu Kobayashi, Masanao Obayashi, 2013, Robotics.

A reinforcement learning system for swarm behaviors

Kunikazu Kobayashi, Masanao Obayashi, Takashi Kuremoto, 2008, 2008 IEEE International Joint Conference on Neural Networks (IEEE World Congress on Computational Intelligence).

Adaptive Swarm Behavior Acquisition Using a Neuro-Fuzzy Reinforcement Learning System

Kunikazu Kobayashi, Masanao Obayashi, Takashi Kuremoto, 2013 .

A Bayesian Local Linear Wavelet Neural Network

Kunikazu Kobayashi, Masanao Obayashi, Takashi Kuremoto, 2009, ICONIP.

A Local Linear Wavelet Neural Network Based on a Bayesian Design Method

Kunikazu Kobayashi, Masanao Obayashi, Takashi Kuremoto, 2009 .

Deep Belief Network Using Reinforcement Learning and Its Applications to Time Series Forecasting

Shingo Mabu, Kunikazu Kobayashi, Masanao Obayashi, 2016, ICONIP.