Learning Systems with FUZZY

Fuzzy techniques have been proven to effectively tackle the problems of uncertainty in relationships among variables in systems that learn to adapt to a changing environment. This paper outlines our challenges for the last 25 years to design learning systems with fuzzy techniques and their applications to many real world problems. We then focus on the development of human-in-the-loop systems, such as a smart home or an assistive robotic environment, that involve different types of learning strategies. This warrants a full consideration of learning mechanisms in humans that mediate action-selection. We envisage that the principles of fuzzy theory, when combined with what we know about computational learning mechanisms in the human brain, will offer a practical guidance on how we design learning systems to advance user’s experience in real-world scenarios.

[1]  Z. Zenn Bien,et al.  Neural network-based fuzzy observer with application to facial analysis , 2000, Pattern Recognit. Lett..

[2]  Z. Zenn Bien,et al.  Applying human learning principles to user-centered IoT systems , 2013, Computer.

[3]  Sang Wan Lee,et al.  Adaptive Gabor Wavelet Neural Network for Facial Expression Recognition - Training of Feature Extractor by Novel Feature Separability Criterion , 2005 .

[4]  Z. Zenn Bien,et al.  A dynamic gesture recognition system for the Korean sign language (KSL) , 1996, IEEE Trans. Syst. Man Cybern. Part B.

[5]  Z. Zenn Bien,et al.  A gray-level corner detector using fuzzy logic , 1996, Pattern Recognit. Lett..

[6]  Z. Zenn Bien,et al.  Design of the fuzzy multiobjective controller based on the eligibility method , 2003, Int. J. Intell. Syst..

[7]  Z. Zenn Bien,et al.  Development of Assistive Software for Disabled and Aged People Based on User Characteristics - Unified User Interface for Special Work Chair , 2007 .

[8]  Z. Zenn Bien,et al.  Design of “Personalized” Classifier Using Soft Computing Techniques for “Personalized” Facial Expression Recognition , 2008, IEEE Transactions on Fuzzy Systems.

[9]  Z. Zenn Bien,et al.  Stability of TSK-Type Time-Delay FLC , 2002, Intell. Autom. Soft Comput..

[10]  Shinsuke Shimojo,et al.  Neural Computations Underlying Arbitration between Model-Based and Model-free Learning , 2013, Neuron.

[11]  Michael D. Ehlers,et al.  Breaching the Blood-Brain Barrier for Drug Delivery , 2014, Neuron.

[12]  Huaguang Zhang,et al.  A fuzzy basis function vector-based multivariable adaptive controller for nonlinear systems , 2000, IEEE Trans. Syst. Man Cybern. Part B.

[13]  Z. Zenn Bien,et al.  KARES: Intelligent wheelchair-mounted robotic arm system using vision and force sensor , 1999, Robotics Auton. Syst..

[14]  Tomomasa Sato,et al.  Dynamic footprint‐based person recognition method using a hidden markov model and a neural network , 2004, Int. J. Intell. Syst..

[15]  Z. Zenn Bien,et al.  Robust self-learning fuzzy controller design for a class of nonlinear MIMO systems , 2000, Fuzzy Sets Syst..

[16]  Jong-Tae Lim,et al.  Robotic smart house to assist people with movement disabilities , 2007, Auton. Robots.

[17]  Samuel M. McClure,et al.  Temporal Prediction Errors in a Passive Learning Task Activate Human Striatum , 2003, Neuron.

[18]  Z. Zenn Bien,et al.  A Steward Robot for Human-Friendly Human-Machine Interaction in a Smart House Environment , 2008, IEEE Transactions on Automation Science and Engineering.

[19]  Andrew G. Barto,et al.  Reinforcement learning , 1998 .

[20]  P. Ekman,et al.  Unmasking the Face: A Guide to Recognizing Emotions From Facial Expressions , 1975 .

[21]  Z. Zenn Bien,et al.  Programming Approach for Fuzzy Model-Based Multiobjective Control Systems , 1999, Int. J. Uncertain. Fuzziness Knowl. Based Syst..

[22]  Z. Zenn Bien,et al.  Soft computing based intention reading techniques as a means of human-robot interaction for human centered system , 2003, Soft Comput..

[23]  Jin-Woo Jung,et al.  Realization of Personalized Services for Intelligent Residential Space based on User Identification Method using Sequential Walking Footprints , 2005 .

[24]  Jun-Hyeong Do,et al.  Intelligent Interaction For Human-Friendly Service Robot in Smart House Environment , 2008 .

[25]  Jun-Hyeong Do,et al.  View-invariant hand-posture recognition for soft-remocon-system , 2004, 2004 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (IEEE Cat. No.04CH37566).

[26]  Peter Dayan,et al.  A Neural Substrate of Prediction and Reward , 1997, Science.

[27]  Z. Zenn Bien,et al.  Beat gesture recognition and finger motion control of a piano playing robot for affective interaction of the elderly , 2008, Intell. Serv. Robotics.

[28]  Zeungnam Bien,et al.  A Study on the Application of the Software Framework MASSIVE in KAIST's Intelligent Sweet Home System , 2008 .

[29]  Z. Zenn Bien,et al.  An inference network for bidirectional approximate reasoning based on an equality measure , 1994, IEEE Trans. Fuzzy Syst..

[30]  Z. Zenn Bien,et al.  Gesture Spotting Using Fuzzy Garbage Model and User Adaptation , 2011, Int. J. Fuzzy Syst. Appl..

[31]  P. Dayan,et al.  States versus Rewards: Dissociable Neural Prediction Error Signals Underlying Model-Based and Model-Free Reinforcement Learning , 2010, Neuron.

[32]  Z. Zenn Bien,et al.  A Nonsupervised Learning Framework of Human Behavior Patterns Based on Sequential Actions , 2010, IEEE Transactions on Knowledge and Data Engineering.

[33]  Myung-Geun Chun,et al.  Neurocomputational approach to solve a convexly combined fuzzy relational equation with generalized connectives , 1993 .

[34]  Z. Zenn Bien,et al.  Hand Gesture Recognition Using Multivariate Fuzzy Decision Tree and User Adaptation , 2011, Int. J. Fuzzy Syst. Appl..

[35]  Jun-Hyeong Do,et al.  Intention reading is essential in human-friendly interfaces for the elderly and the handicapped , 2005, IEEE Transactions on Industrial Electronics.

[36]  Zeung nam Bien.  Multi-Resolution Fuzzy Min-Max Neural Network with On-line Learning Ability Using Mixture of Experts , 2004 .

[37]  Dong-Soo Kwon,et al.  Integration of a Rehabilitation Robotic System (KARES II) with Human-Friendly Man-Machine Interaction Units , 2004, Auton. Robots.

[38]  D.H. Stefanov,et al.  The smart house for older persons and persons with physical disabilities: structure, technology arrangements, and perspectives , 2004, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[39]  Zeung nam Bien,et al.  Incremental Inductive Learning Algorithm in the Framework of Rough Set Theory and its Application , 1998 .

[40]  Takeo Kanade,et al.  Facial Expression Recognition , 2011, Handbook of Face Recognition.

[41]  Dae-Jin Kim,et al.  A novel feature selection for fuzzy neural networks for personalized facial expression recognition , 2004 .

[42]  Z. Zenn Bien,et al.  Robust EMG pattern recognition to muscular fatigue effect for powered wheelchair control , 2009, J. Intell. Fuzzy Syst..

[43]  Z. Zenn Bien,et al.  Recognition of Continuous Korean Sign Language Using Gesture Tension Model and Soft Computing Technique , 2004, IEICE Trans. Inf. Syst..

[44]  Z. Zenn Bien,et al.  Design of Fuzzy Logic Controller with Inconsistent Rule Base , 1994, J. Intell. Fuzzy Syst..

[45]  Z. Zenn Bien,et al.  Feature subset selection using separability index matrix , 2013, Inf. Sci..