
Intelligence Science II
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The 44 full papers and 5 short papers presented were carefully reviewed and selected from 85 submissions. They deal with key issues in intelligence science and have been organized in the following topical sections: brain cognition; machine learning; data intelligence; language cognition; perceptual intelligence; intelligent robots; fault diagnosis; and ethics of artificial intelligence.
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Content
- Intro
- Preface
- Organization
- Brain Cognition
- Abstracts of Keynote and Invited Talks
- Progress Toward a High-Performance Brain Interface
- Predicting the Present: Experiments and Computational Models of Perception and Internally Generated Representations
- Brain Science and Artificial Intelligence
- Intelligence Science Will Lead the Development of New Generation of Artificial Intelligence
- Scientific Paradigm Shift for Intelligence Science Research
- Visual Information Processing - From Video to Retina
- The Human Brainnetome Atlas and Its Applications in Neuroscience and Brain Diseases
- A Brief Overview of Practical Optimization Algorithms in the Context of Relaxation
- Clifford Geometric Algebra
- Urban Computing: Building Intelligent Cities Using Big Data and AI
- New Approaches to Natural Language Understanding
- Neuromorphic Computing: A Learning and Memory Centered Approach
- Theory of Cognitive Relativity
- Two-layer Mixture of Gaussian Processes for Curve Clustering and Prediction
- Contents
- Multi-task Motor Imagery EEG Classification Using Broad Learning and Common Spatial Pattern
- Abstract
- 1 Introduction
- 2 Methods
- 2.1 Multiclass Common Spatial Pattern
- 2.2 Broad Learning
- 2.3 Our Algorithm
- 3 Experiments and Discussion
- 3.1 Datasets and Settings
- 3.2 Experimental Results
- 3.3 Discussion
- 4 Conclusion
- References
- From Bayesian Inference to Logical Bayesian Inference
- Abstract
- 1 Introduction
- 2 From Bayes' Prediction to Logical Bayesian Inference
- 3 Mathematical Basis: Three Kinds of Probabilities and Three Kinds of Bayes' Theorems
- 4 Logical Bayesian Inference (LBI)
- 5 Logical Bayesian Inference for Machine Learning
- 6 Confirmation Measure b* for Induction
- 7 Summary
- References
- Solution of Brain Contradiction by Extension Theory
- Abstract
- 1 Introduction
- 2 From Vector Distance to the Dependent Functions
- 3 Neural Solution of Boolean Function by Dependent Function k´(x)
- 4 Machine and Systems by Nonlinear Neuron
- 5 Conclusions
- Acknowledgments
- References
- Cognitive Features of Students Who Are Tired of Learning Geometry
- Abstract
- 1 Introduction
- 2 Cognitive Features and Interests of Students Who Are Tired of Geometry Learning
- 3 Way to Transform Geometry Learning from the Perspective of Interest for Students
- 4 Case Study
- 5 Conclusion
- Reference
- Machine Learning
- Semantic Channel and Shannon's Channel Mutually Match for Multi-label Classification
- Abstract
- 1 Introduction
- 2 Mathematical Methods
- 2.1 Distinguishing Statistical Probability and Logical Probability
- 2.2 Three Kinds of Bayes' Theorems
- 2.3 From Shannon's Channel to Semantic Channel
- 2.4 To Define Semantic Information with Log (Normalized Likelihood)
- 3 Multi-label Classification for Visibal Instances
- 3.1 Multi-label Learning (the Receiver's Logical Classification) for Truth Functions Without Parameters
- 3.2 Selecting Examples for Atomic Labels' Learning
- 3.3 Multi-label Learning for Truth Functions with Parameters
- 3.4 Multi-label Selection (the Sender's Selective Classification)
- 3.5 Classifier h(X) Changes with P(X) to Overcome Class-Imbalance Problem
- 4 The CM Iteration Algorithm for the Multi-label Classification of Unseen Instances
- 5 Summary
- References
- Exploiting the Similarity of Top 100 Beauties for Hairstyle Recommendation via Perceptual Hash
- Abstract
- 1 Introduction
- 2 Related Work
- 3 Proposed Hairstyle Recommendation System
- 3.1 Overall Framework
- 3.2 Data Collection and Pre-handling
- 3.3 Perceptual Hash Based Recommendation
- 3.4 Haar Feature Classified
- 4 Implementation
- 4.1 Programming Language
- 4.2 Critical Persuade Code for Hairstyle Recommendation
- 5 Results and Analysis
- 6 Conclusion
- Acknowledgement
- References
- Attribute Coordinate Comprehensive Evaluation Model Combining Principal Component Analysis
- Abstract
- 1 Introduction
- 2 Reduction of Indicators by Principal Component Analysis
- 3 Attribute Coordinate Comprehensive Evaluation Model
- 3.1 Explore Barycentric Coordinates Reflecting Evaluators' Preference Weight
- 3.2 Calculate the Most Satisfactory Solution
- 4 Simulation Experiment
- 4.1 Attribute Coordinate Comprehensive Evaluation Without Using Principal Component Analysis
- 4.2 Attribute Coordinate Comprehensive Evaluation with Principal Component Analysis
- 5 Conclusion
- References
- A Specialized Probability Density Function for the Input of Mixture of Gaussian Processes
- 1 Introduction
- 2 GP and MGP Models
- 2.1 GP Model
- 2.2 MGP Model
- 3 Specialized Input Distribution and Its Learning Algorithm
- 3.1 Specialized PDF
- 3.2 Learning Algorithm for the Specialized PDF
- 4 The MGP Model of the Specialized PDFs and Its Learning Algorithm
- 5 Experimental Results
- 5.1 Simulation Experiments
- 5.2 Prediction on Stock Data
- 6 Conclusion
- References
- Research of Port Competitiveness Evaluation Based on Attribute Evaluation Method
- Abstract
- 1 Introduction and Literature Review
- 2 Attribute Coordinate Comprehensive Evaluation Method
- 3 Attribute Characteristics of Port Competitiveness
- 4 Port Competitiveness Index System
- 5 Empirical Study
- 6 Conclusion
- References
- Universal Learning Machine - Principle, Method, and Engineering Model Contributions to ICIS 2018
- 1 Introduction
- 2 Universal Learning Machine
- 3 Subjective Pattern and X-form
- 3.1 Objective Pattern
- 3.2 Subjective Pattern
- 3.3 X-form
- 3.4 Discussions About X-form
- 4 Conceiving, Governing and Primary Consciousness
- 5 Learning Dynamics and Data Sufficiency
- 6 Learning Strategies
- 7 Engineering Model
- References
- An Improved CURE Algorithm
- Abstract
- 1 Introduction
- 2 Related Work
- 3 Improved CURE Algorithm
- 3.1 Sample Extraction
- 3.2 Representative Point Selection
- 3.3 The ISE-RS-CURE Algorithm
- 4 Experiment Analysis
- 4.1 Experiments on Synthetic Data Sets
- 4.2 Experiments on the Real Data Sets
- 5 Conclusion
- References
- Data Intelligence
- D-JB: An Online Join Method for Skewed and Varied Data Streams
- 1 Introduction
- 2 Related Work
- 3 Preliminaries
- 3.1 Concept Description
- 3.2 Optimization Objective
- 4 D-JB Model Design
- 4.1 D-JB Architecture
- 4.2 Algorithms of Data Migration
- 5 Evaluation
- 5.1 Experimental Setup
- 5.2 Throughput and Latency
- 5.3 Scalability
- 6 Conclusion
- References
- The Application of Association Analysis in Mobile Phone Forensics System
- Abstract
- 1 Introduction
- 2 The Analysis of Intimacy Based on Clustering
- 2.1 Traditional Clustering Method
- 2.2 An Improved K-Means Algorithm
- 2.2.1 The Choice of Initial Cluster Centre
- 2.2.2 The Pre-processing of the Isolated Points
- 3 An Improved Association Analysis Algorithm
- 3.1 The Basic Concepts of Association Rule Mining
- 3.2 Apriori Algorithm and Its Improvement
- 4 Experiment and Results
- 4.1 The Results of the Intimacy Analysis
- 4.2 The Results of Association Rule Mining
- 5 Conclusions
- References
- How to Do Knowledge Module Finishing
- Abstract
- 1 Introduction
- 2 Method
- 2.1 The Scientific Principles on Which This Method Is Based
- 2.2 Taking the Formal Study of the Ideology of "Ruling the Country" as an Example
- 2.3 Expert Knowledge of Human-Computer Collaboration System Platform
- 3 Result
- 4 Conclusion
- References
- The Art of Human Intelligence and the Technology of Artificial Intelligence: Artificial Intelligence Visual Art Research
- Abstract
- 1 Introduction
- 2 Related Work
- 2.1 Creativity in AI Art
- 2.2 Art Standard in AI Art
- 2.3 Art Reception in AI Art
- 3 Conclusion
- Acknowledgement
- References
- Language Cognition
- Using Two Formal Strategies to Eliminate Ambiguity in Poetry Text
- Abstract
- 1 Introduction
- 2 Related Work
- 2.1 Build a Double-Words Chessboard and Chinese Language Chessboard Spectrum
- 2.2 Experiments
- 2.3 Public Datasets
- 3 Discussion
- 4 Future Work
- Acknowledgement
- References
- Discussion on Bilingual Cognition in International Exchange Activities
- 1 Introduction
- 2 Background
- 2.1 International Exchange Activities
- 2.2 Neural Machine Translation
- 3 Methodology
- 3.1 HCI Method for International Communication
- 3.2 Mixed Transfer Learning Approach for NMT
- 4 Experiments
- 4.1 Setup
- 4.2 Effect of MTL for Low-Resource NMT
- 5 Related Work
- 6 Conclusion and Future Work
- References
- The Cognitive Features of Interface Language and User Language
- Abstract
- 1 Introduction
- 2 Interface Language
- 3 User Language
- 4 Conclusion
- References
- The Cognitive Features of Programming Language and Natural Language
- Abstract
- 1 Introduction
- 2 Cognitive Features of Programming and Natural Language
- 3 Conclusion
- References
- Ten-Years Research Progress of Natural Language Understanding Based on Perceptual Formalization
- Abstract
- 1 Introduction
- 2 What is the Semantics
- 3 Mechanisms of Understanding
- 3.1 Understanding
- 3.2 Comprehensive Understanding
- 3.3 Understanding Effect
- 4 Several Understanding Mechanism Related Algorithms
- 4.1 Text Understanding Algorithm for Language Machine Understanding
- 4.2 Pragmatic Meaning Derivation Algorithm of Natural Language Machine Understanding
- 4.3 Deductive Reasoning Algorithm Guided by Natural Language Understanding
- 5 Related Work and Prospects
- 5.1 The Natural Language Understanding Basis of Machine Translation
- 5.2 Machine Learning Based on Natural Language Understanding
- 5.3 The Physiological Basis of the Invariance of Perceptual Properties
- 5.4 Visual Turing Test and Intelligence Definition
- References
- Learning Word Sentiment with Neural Bag-Of-Words Model Combined with Ngram
- 1 Introduction
- 2 Related Work
- 3 Neural Bag-Of-Words (NBOW) Model
- 4 Proposed Model: Neural Bag-Of-Words-Ngram (NBOWN)
- 5 Experiment
- 5.1 Data
- 5.2 Word Embedding and Performance Measure
- 6 Result
- 6.1 Classification Performance
- 6.2 Visualization of Words Sentiment
- 7 Conclusion and Future Work
- References
- Related Text Discovery Through Consecutive Filtering and Supervised Learning
- 1 Introduction
- 2 Methodology
- 3 Experimental Results
- 3.1 Data Sets
- 3.2 Text Representation
- 3.3 Feature Selection
- 3.4 Performance Measures
- 3.5 Parameter Setting
- 3.6 Performances and Comparisons
- 4 Conclusion
- References
- Natural Language Semantics and Its Computable Analysis
- 1 Introduction
- 2 The Meaning of Natural Language
- 3 The Intensional Logic
- 4 Conclusion
- References
- Can Machines Think in Radio Language?
- 1 Introduction
- 2 The Principle of Language's Relativity
- 3 Significance of the Principle for Intelligence
- 4 Conclusion
- References
- Language Understanding of the Three Groups of Connections: Management Innovation Dynamic Mechanism a ...
- Abstract
- 1 Introduction
- 1.1 Background
- 1.2 Purpose
- 2 Research on Management Innovation Dynamic Mechanism
- 2.1 Theoretical Discussion
- 2.2 Theoretical Construction
- 3 The Creation of Intelligent Driving Environment
- 3.1 Actual Build: Environment
- 3.2 Actual Optimization: Intelligent
- 4 Conclusion
- 4.1 Dynamic Mechanism and Driving Environment
- 4.2 Significance
- References
- Perceptual Intelligence
- CSSD: An End-to-End Deep Neural Network Approach to Pedestrian Detection
- Abstract
- 1 Introduction
- 2 CSSD
- 2.1 Backbone Network
- 2.2 Circular Feature Pyramid
- 2.3 Connection Modules
- 2.4 Training Objective
- 3 Experiments
- 3.1 Dataset and Evaluation
- 3.2 Training, Testing Settings and Results
- 4 Results Analysis
- 4.1 Effectiveness Analysis
- 4.2 Runtime Analysis
- 5 Conclusions
- References
- Predicting Text Readability with Personal Pronouns
- Abstract
- 1 Introduction
- 2 Materials and Methodology
- 2.1 Corpus Data
- 2.2 Readability Formula
- 3 Data Processing
- 4 Results and Discussion
- 4.1 Readability Results of Random Texts of Nine Genres
- 4.2 Fitness Results
- 5 Reevaluation for Strong Fitting Subsets
- 6 Conclusion
- References
- The Influence of Facial Width-to-Height Ratio on Micro-expression Recognition
- Abstract
- 1 Introduction
- 1.1 Micro-expressions of Emotion
- 1.2 Facial Width-to-Height Ratio (FWHR)
- 2 The Current Study: Effects of Facial Width-to-Height Ratio on the Recognition Micro-expressions
- 3 Method
- 3.1 Participants and Design
- 3.2 Stimuli
- 4 Apparatus and Procedure
- 5 Results
- 6 Discussion
- Acknowledgements
- References
- Shortest Paths in HSI Space for Color Texture Classification
- 1 Introduction
- 2 Model Texture to Graph
- 2.1 Graph and Shortest Path
- 2.2 Modeling Texture to Graph
- 2.3 Edge Weight Analysis
- 3 Express Color Texture Features with the Shortest Path
- 4 Experiment and Results
- 5 Conclusion
- References
- The 3D Point Clouds Registration for Human Foot
- Abstract
- 1 Introduction
- 2 Method Review
- 2.1 The NARF Key Point
- 2.2 The FPFH Descriptor
- 2.2.1 The PFH Descriptor
- 2.2.2 The Principle of the FPFH Descriptor
- 2.2.3 The Difference of PFH and FPFH
- 2.3 Improved FPFH Descriptors
- 2.4 Registration Based on Descriptors
- 2.4.1 Sample Consensus Initial Alignment
- 2.4.2 Iterative Closest Point (ICP)
- 3 Results and Discussion
- 4 Conclusions
- Acknowledgment
- References
- The Cognitive Philosophical Problems in Visual Attention and Its Influence on Artificial Intelligence Modeling
- Abstract
- 1 Introduction
- 2 Cognitive Philosophical Problems of Visual Attention
- 2.1 What is the Essence of Visual Attention?
- 2.2 What are the Basic Units of Visual Attention?
- 2.3 What are the Factors that Affect the Visual Attention?
- 3 The Computational Model of Visual Attention
- 4 Core Issues and Strategies for Constructing Visual Attention Computational Models
- 4.1 The Basic Unit Selection Problem of Visual Attention Computational Model
- 4.2 Feature Selection of Visual Attention Computational Model
- 4.3 Selection of Multiple Visual Features Fusion Strategies for Visual Attention Computational Models
- 5 Conclusion
- Acknowledgement
- References
- Parallel Dimensionality-Varied Convolutional Neural Network for Hyperspectral Image Classification
- Abstract
- 1 Introduction
- 2 Proposed Method
- 2.1 Dimensionality-Varied CNN
- 2.2 Parallel Computing
- 3 Experiments
- 3.1 Classification Accuracy of Methods×
- 3.2 Time Consuming of Methods
- 4 Conclusions
- Acknowledgments
- References
- Model Selection Prediction for the Mixture of Gaussian Processes with RJMCMC
- 1 Introduction
- 2 The Mixture of Gaussian Processes and Its Latent Variables
- 3 Model Selection Prediction with Reversible Jump Markov Chains Monte Carlo
- 3.1 The Moves with the Component Number Fixed for (a)(b)(c)
- 3.2 The Moves with the Component Number Changed
- 3.3 Metropolis-Hastings Update
- 4 Convergence Diagnosing
- 5 Conclusion
- References
- Intelligent Robot
- Self-developing Proprioception-Based Robot Internal Models
- 1 Introduction
- 2 Developing the Internal Models
- 2.1 Developing the Proprioception
- 2.2 Developing the Forward Model
- 2.3 Developing the Inverse Model
- 3 Experiments
- 3.1 Development of Proprioception
- 3.2 Comparison of the Forward Models
- 3.3 Comparison of the Inverse Models
- 3.4 Evaluation of the Integrated Internal Models
- 4 Conclusion
- References
- Artificial Unintelligence: Anti-intelligence of Intelligent Algorithms
- 1 Introduction
- 2 Value Creation From Big Data
- 2.1 Core Value of Big Data
- 2.2 Demonstration of Data Value
- 2.3 No Free Lunch Theorem
- 2.4 Role of Artificial Intelligence Algorithms
- 3 Anti-intelligence Features of AI Algorithms
- 3.1 Tendency of `fatuous King'
- 3.2 Generalization of Quick Thinking
- 3.3 Retribalization of the Digital Age
- 4 Countermeasures and Conclusions
- References
- XiaoA: A Robot Editor for Popularity Prediction of Online News Based on Ensemble Learning
- 1 Introduction
- 2 Related Work
- 3 Preliminaries
- 3.1 Problem Statement
- 3.2 Original Dataset
- 3.3 Data Preprocessing
- 4 Proposed Methodology
- 4.1 Component Learners
- 4.2 Ensemble Learning
- 5 Experiments
- 6 Conclusion
- References
- Design and Implementation of Location Analysis System for Mobile Devices
- Abstract
- 1 Introduction
- 2 System Related Technologies
- 2.1 NodeJS
- 2.2 Bootstrap
- 2.3 Tencent Map API
- 3 Design and Implementation of Geographical Analysis System of Mobile Terminal Equipment
- 3.1 System Front-End Interface Design and Implementation
- 3.2 Design and Implementation of System Front-End Logical Functions
- 3.3 The Backend Logic Function of This System is Realized Through NodeJS
- 4 Conclusion
- References
- Control Information Acquisition and Processing of the AMT System Based in LabVIEW and MATLAB
- Abstract
- 1 Introduction
- 2 Overview of Data Acquisition and Process Techniques
- 3 Interface of the DAQ System
- 4 Data Processing and Results Presentation
- 5 Conclusions
- Acknowledgement
- References
- Multi-robot Distributed Cooperative Monitoring of Mobile Targets
- Abstract
- 1 Introduction
- 2 Problem Description
- 3 Distributed Cooperative Path Planning Algorithm
- 3.1 Distributed Robot Selection Method
- 3.2 Multi-robot Distributed Cooperative Path Planning Algorithm
- 4 Comparative Experiment
- 4.1 Experimental Results
- 4.2 Dynamic Decision Sequence Versus Fixed Decision Sequence
- 5 Conclusion
- Acknowledgment
- References
- Research on the Micro-blog User Behavior Model Based on Behavior Matrix
- Abstract
- 1 Introduction
- 2 Micro-blog User Behavior Model Based on Behavior Matrix
- 2.1 Behavior Matrix Model
- 2.2 The Analysis Method of Behavior Matrix
- 3 Experimental Analysis
- 4 Conclusions
- References
- Probe Machine Based Consecutive Route Filtering Approach to Symmetric Travelling Salesman Problem
- 1 Introduction
- 2 Related Work
- 3 Proposed Algorithm
- 3.1 Probe Concept
- 3.2 Working Steps
- 3.3 Filtering Proportion in Each Step
- 4 Experimental Results
- 5 Conclusion and Future Research
- References
- Fault Diagnosis
- Automatic Fault Detection for 2D Seismic Data Based on the Seismic Coherence of Mutative Scale Analysis Window
- 1 Introduction
- 2 Conventional Seismic Coherence
- 2.1 Semblance Coherence
- 2.2 Eigenstrcture-Based Coherence
- 3 Proposed Seismic Coherence of Mutative Scale Analysis Window
- 4 Fault Detection Through the Proposed Coherence
- 5 Experimental Results
- 6 Conclusion
- References
- UAV Assisted Bridge Defect Inspection System
- Abstract
- 1 Introduction
- 2 Related Work
- 3 Electromechanics and Communication System
- 3.1 Navigation
- 3.2 Flight Control
- 3.3 Image Capture
- 3.4 Communication
- 3.5 Self-protection Mechanism
- 4 Image Processing
- 4.1 Gradient Processing
- 4.2 Gray-Scale Stretch
- 4.3 Fisher Thresholding
- 4.4 Clustering Analysis
- 4.5 Experimental Results
- 5 Conclusion
- References
- Fault Diagnosis and Knowledge Extraction Using Fast Logical Analysis of Data with Multiple Rules Discovery Ability
- Abstract
- 1 Introduction
- 2 Logical Analysis of Data
- 3 Fast LAD with Multiple Rules Discovery Ability
- 3.1 Multiple Rules Discovery Based on Modified MILP
- 3.2 Fast LAD Based on Fast Data Binarization
- 4 A Case Study on Tennessee Eastman Process
- 5 Conclusions
- Acknowledgements
- References
- Improved Feature Selection Algorithm for Prognosis Prediction of Primary Liver Cancer
- Abstract
- 1 Introduction
- 2 Principle
- 2.1 Decision Tree Algorithm
- 2.1.1 Information Gain
- 2.1.2 Gain Rate
- 2.1.3 Gini Index
- 2.2 Random Forest Algorithm
- 2.3 Improved Feature Selection Algorithm
- 3 Experimental Analysis
- 3.1 Collection and Data Collation
- 3.2 Comparison Between Decision Tree and Random Forest
- 4 Conclusion
- References
- A Novel Spatial-Spectra Dynamics-Based Ranking Model for Sorting Time-Varying Functional Networks from Single Subject FMRI Data
- Abstract
- 1 Introduction
- 2 Theory and Methods
- 2.1 Brief Review of Quasi-GICA
- 2.2 Weighted BFNs Ranking Model
- 3 Experimental Tests
- 3.1 Experimental Datasets
- 3.2 Data Processing
- 4 Results and Analysis
- 4.1 Results of Dynamic Low-Frequency Fluctuations
- 4.2 Results of Dynamic Spatial Reproducibility
- 4.3 Results of Weighted BFNs Ranking
- 5 Discussion
- 6 Conclusion
- Acknowledgments
- References
- Bat Algorithm with Individual Local Search
- Abstract
- 1 Instruction
- 2 Bat Algorithm
- 3 Bat Algorithm with Individual Local Search
- 4 Experiments
- 4.1 Investigation of Parameter r
- 4.2 Comparison with State-of-Art Algorithms
- 5 Conclusion
- Acknowledgements
- References
- Ethics of Artificial Intelligence
- Research on Artificial Intelligence Ethics Based on the Evolution of Population Knowledge Base
- Abstract
- 1 Dilemma for Formation of Human and Artificial Intelligence Ethics
- 2 Inspiration of New Technological Advances on the Development Direction of Human Society
- 2.1 Evolution of Biological Brain for Hundreds of Millions of Years
- 2.2 Formation and Evolution of the Internet Brain
- 2.3 Division and Evolution of Intelligence Levels
- 3 Development Direction of Human Society - Judged with the Population Knowledge Base
- 4 Discussion on the Construction and Decision of AI Ethics from the Perspective of Development Direction of Human Society
- 4.1 Taking the Evolution from the Population Knowledge Base as a Standard for Constructing AI Ethics
- 4.2 Discussion on the Decision of Viewing AI Ethics from the Perspective of Evolution
- 5 Summary
- References
- Does AI Share Same Ethic with Human Being?
- Abstract
- 1 Introduction
- 2 The Problem of Abstract Moral Law and AI
- 3 Three Stages of Virtue Ethics of Macintyre and AI
- 4 AI and the Recognition of Society
- 5 Conclusion
- References
- "Machinery Rationality" Versus Human Emotions: Issues of Robot Care for the Elderly in Recent Sci-Fi Works
- Abstract
- 1 Introduction
- 1.1 A Brief Literature Review
- 1.2 Five Ethical Issues in the New Era of HRI
- 2 The Machinery Rationality Versus Human Emotions
- 2.1 The Elderly as An Irrational Group
- 2.2 The New Conflicts Between Human and Robot
- 3 Robot as Antithesis: The Irrationality of Human Beings
- 3.1 Robot: Not "It" But "He"
- 3.2 The Intimate HRI and the Risk
- 3.3 The Irrationality of Human Being in the Mirror of Robots
- 4 Conclusion and Prospect
- References
- Correction to: From Bayesian Inference to Logical Bayesian Inference
- Correction to: Chapter "From Bayesian Inference to Logical Bayesian Inference: A New Mathematical Frame for Semantic Communication and Machine Learning" in: Z. Shi et al. (Eds.): Intelligence Science II, IFIP AICT 539, https://doi.org/10.1007/978-3-030-01313-4_2
- Author Index
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