Intelligent Systems: Concepts and Applications

Published in honour of the 70th birthday of Yoh-Han Pao, George S. Dively Dis- tinguished Professor of Engineering at Case Western Reserve University, Cleveland, Ohio, this festschrift embraces a remarkably diverse set of topics. Drawing from the fields of pattern recognition, engineering, artificial intelligence and artificial neural systems, it is a fitting testament to the extraordinary breadth of his professional in- terests both in foundational research into the new technology of Intelligent Systems and ill the application of that evolving technology to the solution of hard engineering problems. In common with many scientists who build their reputations in one field before devoting their considerable energies and talents to another one, by 1972, the year in which I met him for the first time, Yoh-Han had made significant contributions to laser technology, in particular to the development of the highly accurate and stable lasers required for holographic recording purposes. In conventional holography, the information stored in a hologram produces a virtual image of the object charac- terised by it. However, Yoh-Han became fascinated by the possiblity of driving the process hackwards, of using the hologram as an associative memory device enabling previously stored information to be retrieved on the basis of partial cues. It was this burgeoning interest which shaped his career for more than twenty years. Just prior to 1972, my colleagues Professor Christopher Longuet-Higgins and Dr.

Table of Contents:
1 Knowledge, Learning and Machine Intelligence.- 1.1 Introduction.- 1.2 Special Boxes for Special Tricks.- 1.3 Schools of AI.- 1.4 Tacit “Thinking ”.- 1.5 What Is a “Concept ”?.- 1.6 A Homework on “Making Clear ”.- 1.7 Formal Logic as a Tool for Thinking.- 1.8 Drug Design by Machine Learning.- 1.9 Visualization in Mathematical Thinking: Limitations of Logic.- 1.10 Mental Manipulation of Images.- 1.11 Thinking Without Thinking.- 1.12 Piloting a Flight Simulator.- 1.13 Conclusion.- References.- 2 Relating Images, Concepts, and Words.- 2.1 Introduction.- 2.2 Development of Perceptual Representation Schemes.- 2.3 Processing Implications.- 2.4 Evidence from Language for Different Kinds of Mappings.- 2.5 Large Scale Analogies.- 2.6 An Example of Representation Using Prototypes.- 2.7 Mapping.- 2.8 Assessment.- 2.9 Problems Remaining.- References.- 3 Methods for an Expert System to Access an External Database.- 3.1 Introduction.- 3.2 An Expert System for Motor Selection.- 3.3 A More Flexible Inference Engine.- 3.4 Discussion.- References.- 4 Perceptual Representation and Reasoning.- 4.1 Introduction.- 4.2 Perceptual Reasoning.- 4.3 Discussion.- References.- 5 Feature Based, Collision Free Inspection Path Planning.- 5.1 Background.- 5.2 Configuration Space.- 5.3 Inspection Path Planning Problem.- 5.4 Inspection Path Planning Algorithm.- 5.5 Inspection Path Planning.- 5.6 Conclusions.- References.- 6 Of Using Constraint Logic Programming for Design of Mechanical Parts.- 6.1 Introduction.- 6.2 Symbolic Descriptions with Constraints.- 6.3 Reasoning about Dimensions and Tolerances.- 6.4 Checking Design Rules.- 6.5 Conclusions.- References.- 7 Explanation Facility for Neural Networks.- 7.1 Introduction.- 7.2 Neural Network Explanations.- 7.3 Prolog Code.- 7.4 Example.-7.5 Implementation and Improvements.- 7.6 Conclusions.- References.- 8 Compile-Time Type Prediction and Type Checking for Common Lisp Programs.- 8.1 Introduction.- 8.2 The Type System.- 8.3 The Representation of Programs.- 8.4 Type Inference Rules.- 8.5 The Inference System.- 8.6 Examples.- 8.7 Related Work.- 8.8 Conclusion.- References.- 9 Cognitive Neuroethology: An Approach to Understanding Biological Neural Networks.- 9.1 Introduction.- 9.2 Determining Neural States.- 9.3 Determining Mental States from Neural and Behavioral States.- 9.4 Predicting Mental States from Neural and Behavioral States.- 9.5 Critique.- 9.6 Summary and Conclusions.- References.- 10 Generating Polytope Intersection Configurations from a Symbolic Description Using CLP(?).- 10.1 Introduction.- 10.2 Problem Formulation.- 10.3 Constraint Logic Programming.- 10.4 Notation.- 10.5 Algorithm.- 10.6 Implementation.- 10.7 Results and Conclusions.- References.- 11 Agent: A Modelling and Analytical Tool for VLSI System Architects.- 11.1 Introduction.- 11.2 The SP.1.- 11.3 Behavior.- 11.4 Structure.- 11.5 Physical Plan.- 11.6 Synthesis and Analysis.- 11.7 Conclusion.- References.