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Knowledge representation is perhaps the most central problem confronting artificial intelligence. Expert systems need knowledge of their domain of expertise in order to function properly. Computer vlslOn systems need to know characteristics of what they are "seeing" in order to be able to fully interpret scenes. Natural language systems are invaluably aided by knowledge of the subject of the natural language discourse and knowledge of the participants in the discourse. Knowledge can guide learning systems towards better understanding and can aid problem solving systems in creating plans to solve various problems. Applications such as intelligent tutoring. computer-aided VLSI design. game playing. automatic programming. medical reasoning. diagnosis in various domains. and speech recogOltlOn. to name a few. are all currently experimenting with knowledge-based approaches. The problem of knowledge representation breaks down into several subsidiary problems including what knowledge to represent in a particular application. how to extract or create that knowledge. how to represent the knowledge efficiently and effectively. how to implement the knowledge representation scheme chosen. how to modify the knowledge in the face of a changing world. how to reason with the knowledge. and how tc use the knowledge appropriately in the creation of the application solution. This volume contains an elaboration of many of these basic issues from a variety of perspectives.
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CONTRIBUTED BY DR. ANTHONY C. HEARN THE RAND CORPORATION, SANTA MONICA, CALIFORNIA REDUCE is a computer program for algebraic computation that IS III world-wide use by thousands of scientists, engineers, and mathematicians. Although it traces its beginnings to 1963, until recently it has only been available on main-frame computers because of its relatively large resource requirements. In 1980 I predicted (1) that by the mid-1980's it would be possible to obtain personal computers in the $10,000 $20,000 range capable of running REDUCE. I am therefore delighted to see that machines of the power of the IBM PC can now run this system, even though these computers are more modestly priced than my 1980 vision of the personal algebra machine. In addition to the need for the more widespread access that personal computers can now provide, there has been a longstanding need for a textbook to help the beginning user become better acquainted with the system. I am therefore very glad that Dr. Rayna has undertaken to write such a book, just as the era of the REDUCE personal algebra machine is beginning. In order to understand the nature of REDUCE, a little history is in order. In 1963 I met Dr. John McCarthy, the inventor of LISP.
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This book is about reasoning with causal associations during diagnostic problem-solving. It formalizes several currently vague notions of abductive inference in the context of diagnosis. The result is a mathematical model of diagnostic reasoning called parsimonious covering theory. Within this diagnostic, problems and important relevant concepts are formally defined, properties of diagnostic problem-solving are identified and analyzed, and algorithms for finding plausible explanations in different situations are given along with proofs of their correctness. Another feature of this book is the integration of parsimonious covering theory and probability theory. Based on underlying cause-effect relations, the resulting probabilistic causal model generalized Bayesian classification to diagnostic problems where multiple disorders (faults) may occur simultaneously. Both sequential best-first search algorithms and parallel connectionist (neural network) algorithms for finding the most probable hypothesis are provided. This book should appeal to both theoretical researchers and practitioners.For researchers in artificial intelligence and cognitive science, it provides a coherent presentation of a new theory of diagnostic inference. For engineers and developers of automated diagnostic systems or systems solving other abductive tasks, the book may provide useful insights, guidance, or even directly workable algorithms.
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Making a diagnosis when something goes wrong with a natural or m- made system can be difficult. In many fields, such as medicine or electr- ics, a long training period and apprenticeship are required to become a skilled diagnostician. During this time a novice diagnostician is asked to assimilate a large amount of knowledge about the class of systems to be diagnosed. In contrast, the novice is not really taught how to reason with this knowledge in arriving at a conclusion or a diagnosis, except perhaps implicitly through ease examples. This would seem to indicate that many of the essential aspects of diagnostic reasoning are a type of intuiti- based, common sense reasoning. More precisely, diagnostic reasoning can be classified as a type of inf- ence known as abductive reasoning or abduction. Abduction is defined to be a process of generating a plausible explanation for a given set of obs- vations or facts. Although mentioned in Aristotle's work, the study of f- mal aspects of abduction did not really start until about a century ago.
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Exploration and Innovation in Design is one of the first books to present both conceptual and computational models of processes which have the potential to produce innovative results at early stages of design. Discussed here is the concept of exploration where the system, using computational processes, moves outside predefined available decisions. Sections of this volume discuss areas such as design representation and search, exploration and the emergence of new criteria, and precedent-based adaptation. In addition, the author presents the overall architecture of a design system and shows how the pieces fit together into one coherent system. Concluding chapters of the book discuss relationships of work in design to other research efforts, applications, and future research directions in design. The ideas and processes presented in this volume further our understanding of computational models of design, particularly those that are capable of assisting in the production of non-routine designs, and affirm that we are indeed moving toward a science of design.
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Recent research results in the area of parallel algorithms for problem solving, search, natural language parsing, and computer vision, are brought together in this book. The research reported demonstrates that substantial parallelism can be exploited in various machine intelligence and vision problems. The chapter authors are prominent researchers actively involved in the study of parallel algorithms for machine intelligence and vision. Extensive experimental studies are presented that will help the reader in assessing the usefulness of an approach to a specific problem. Intended for students and researchers actively involved in parallel algorithms design and in machine intelligence and vision, this book will serve as a valuable reference work as well as an introduction to several research directions in these areas.
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Logic grammars have found wide application both in natural language processing and in formal applications such as compiler writing. This book introduces the main concepts involving natural and formal language processing in logic programming, and discusses typical problems which the reader may encounter, proposing various methods for solving them. The basic material is presented in depth; advanced material, involving new logic grammar formalisms and applications, is presented with a view towards breadth. Major sections of the book include: grammars for formal language and linguistic research, writing a simple logic grammar, different types of logic grammars, applications, and logic grammars and concurrency. This book is intended for those interested in logic programming, artificial intelligence, computational linguistics, Fifth Generation computing, formal languages and compiling techniques. It may be read profitably by upper-level undergraduates, post-graduate students, and active researchers on the above-named areas. Some familiarity with Prolog and logic programming would be helpful; the authors, however, briefly describe Prolog and its relation to logic grammars. After reading Logic Grammars, the reader will be able to cope with the ever-increasing literature of this new and exciting field.
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Natural language generation is a field within artificial intelligence which looks ahead to the future when machines will communicate complex thoughts to their human users in a natural way. Generation systems supply the sophisticated knowledge about natural languages that must come into play when one needs to use wordings that will overpower techniques based only on symbolic string manipulation techniques. Topics covered in this volume include discourse theory, mechanical translation, deliberate writing, and revision. Natural Language Generation Systems contains contributions by leading researchers in the field. Chapters contain details of grammatical treatments and processing seldom reported on outside of full length monographs.
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Knowledge representation is perhaps the most central problem confronting artificial intelligence. Expert systems need knowledge of their domain of expertise in order to function properly. Computer vlslOn systems need to know characteristics of what they are "seeing" in order to be able to fully interpret scenes. Natural language systems are invaluably aided by knowledge of the subject of the natural language discourse and knowledge of the participants in the discourse. Knowledge can guide learning systems towards better understanding and can aid problem solving systems in creating plans to solve various problems. Applications such as intelligent tutoring. computer-aided VLSI design. game playing. automatic programming. medical reasoning. diagnosis in various domains. and speech recogOltlOn. to name a few. are all currently experimenting with knowledge-based approaches. The problem of knowledge representation breaks down into several subsidiary problems including what knowledge to represent in a particular application. how to extract or create that knowledge. how to represent the knowledge efficiently and effectively. how to implement the knowledge representation scheme chosen. how to modify the knowledge in the face of a changing world. how to reason with the knowledge. and how tc use the knowledge appropriately in the creation of the application solution. This volume contains an elaboration of many of these basic issues from a variety of perspectives.
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Much water has flowed over the dam since this book went to press in Moscow. One might expect that PIONEER would have made substantial advances-unfortunately it has not. There are reasons: the difficulty of the problem, the disenchantment of the mathematicians (because of the delays and drawing out of the work), and principally the insufficiency and some times complete lack of machine time. The general method used by PIONEER to solve complex multidimen sional search problems had already been formulated at that time. It was supposed that the successful completion of the chess program PIONEER-l would provide a sufficient validation for the method. We did not succeed in completing it. But, unexpectedly, PIONEER's method obtained a different kind of validation. Since our group of mathematicians works at the Institute for Electroen ergy, we were invited to solve some energy-related problems and were assigned the task of constructing a program that would plan the recondi tioning of the equipment in power stations-initially for one month. Until then, the technicians had been preparing such plans without the aid of computers. Although the chess program was not complete even after ten years, the program PIONEER-2 for computing the monthly repair schedule for the Interconnected Power System of Russian Central was completed in a few months. In mid-October of 1980 a medium-speed computer constructed the plan in 40 seconds. When, at the end of the month, the mathematician A.
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Search is an important component of problem solving in artificial intelligence (AI) and, more generally, in computer science, engineering and operations research. Combinatorial optimization, decision analysis, game playing, learning, planning, pattern recognition, robotics and theorem proving are some of the areas in which search algbrithms playa key role. Less than a decade ago the conventional wisdom in artificial intelligence was that the best search algorithms had already been invented and the likelihood of finding new results in this area was very small. Since then many new insights and results have been obtained. For example, new algorithms for state space, AND/OR graph, and game tree search were discovered. Articles on new theoretical developments and experimental results on backtracking, heuristic search and constraint propaga tion were published. The relationships among various search and combinatorial algorithms in AI, Operations Research, and other fields were clarified. This volume brings together some of this recent work in a manner designed to be accessible to students and professionals interested in these new insights and developments.
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8. 5 Summary In this chapter we have identified three basic patterns of influences that lead to ambiguity in the QP analysis of the basic active furnace state. We have then shown how modification of these patterns, by adding equilibrium values and sensitivity annotations on influence arcs, could permit resolu tion of the ambiguities. Finally, we have described in detail the extensions needed to the basic influence resolution algorithm in QP theory to oper ate on these extended descriptions. We have also shown that the modified influence resolution algorithm corrects an error in Forbus' original method for combining influences. We have then presented an extended example in which introduction of equilibrium assumptions eliminates all ambigu ity in the influence resolution deduction. In the next chapter we extend these techniques further, by developing a qualitative perturbation analysis technique that permits us to answer "what ir' control questions; then we extend this technique to obtain quantitative, as well as qualitative, effects of hypothetical control actions. 8.
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Contents: Prologue. - Production Systems and AI. - SearchStrategies for AI Production Systems. - Search Strategiesfor Decomposable Production Systems.- The PredicateCalculus in AI. - Resolution Refutation Systems. -Rule-Based Deduction Systems. - Basic-Plan-GeneratingSystems. - Advanced Plan-Generating Systems. - StructuredObject Representations. - Prospectus. - Bibliography. -Author Index. - Subject Index
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The purpose of this catalogue is to promote interaction between members of the AI' community. It will do this by announcing the existence of Ai techniques and portable software. and acting as a pOinter into the literature. Thus the AI community wili have access to a common. extensional definition of the field. which will: promote a common terminology. discourage the reinvention of wheels. and act as a clearing house for ideas and software. The cataiogue is a reference work providing a quick guide to the AI tools available for different jobs. It is not intended to be a textbook like the Artificial Intelligence Handbook. It. intentionally. only provides a brief description of each tool. with no extended discussion of the historical origin of the tool or how it has been used in particular AI programs, The focus is on techniques abstracted from their historical origins. The original version of the catalogue. was hastily built in 1983 as part of the UK SERC-Dol. IKBS. Architecture Study [lKBS Architecture Study 831. it has now been adopted by the SERC Specially Promoted Programme in IKBS and is kept as an on line document undergoing constant revision and refinement and published as a paperback by Springer Verlag.
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The purpose of the book is to give a unified and comprehensive account of default logic, the most popular logic for those in the Artificial Intelligence (AI) community interested in the formalization of reasoning with incomplete information. The book is mainly concerned with a systematic presentation of the formal theory of default logic, even though the more informal issue of applications of default logic to Artificial Intelligence in general and Knowledge Representation in particular is extensively dealt with, especially by means of many illustrative examples. The book also contains an overview of the other main logics for reasoning in the absence of complete information about the world. The book is intended to be self-contained, so that it is suitable for beginners. As a textbook it is mainly aimed at graduate students for a course on nonmonotonic reasoning. It is also meant to serve as a reference book for AI workers and for researchers in various fields, e.g. Artificial Intelligence, philosophy and cognitive psychology.
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This book discusses the maturity of today's database technology in the light of the needs of engineering applications and industrial automation. Those at the forefront of database research come up with new techniques to satisfy new needs, but today's engineering community must live with database systems that reflect the older state of the art. The purpose of the book is to demonstrate that even though solutions based on today's technology are less than perfect, they do provide solutions to current pressing problems. The book mainly covers current database technology and its applications, but also mentions some promising techniques under research in order to prepare the reader for the future. The book contains four chapters that cover the significance of engineering databases, the current state of database technology, the utilization of engineering databases, and two extensive case studies. For cursory reading, the chapters may be considered to be self-contained. Intended readers are middle management and engineers from industry who deal with automation both as users and vendors, consultants to such industry, vendors of database systems, and lecturers and students.The book requires no special background in informatics.
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The purpose of the book is to give a unified and comprehensive account of default logic, the most popular logic for those in the Artificial Intelligence (AI) community interested in the formalization of reasoning with incomplete information. The book is mainly concerned with a systematic presentation of the formal theory of default logic, even though the more informal issue of applications of default logic to Artificial Intelligence in general and Knowledge Representation in particular is extensively dealt with, especially by means of many illustrative examples. The book also contains an overview of the other main logics for reasoning in the absence of complete information about the world. The book is intended to be self-contained, so that it is suitable for beginners. As a textbook it is mainly aimed at graduate students for a course on nonmonotonic reasoning. It is also meant to serve as a reference book for AI workers and for researchers in various fields, e.g. Artificial Intelligence, philosophy and cognitive psychology.
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Searching is an important process in most AI systems, especially in those AI production systems consisting of a global database, a set of production rules, and a control system. Because of the intractability of uninformed search procedures, the use of heuristic information is necessary in most searching processes of AI systems. This important concept of heuristic informatioD is the central topic of this book. We first use the 8-puzzle and the game tic-tac-toe (noughts and crosses) as examples to help our discussion. The 8-puzzle consists of eight numbered movable tiles set in a 3 x 3 frame. One cell of the frame is empty so that it is possible to move an adjacent numbered tile into the empty cell. Given two tile configurations, initial and goal, an 8-puzzle problem consists of changing the initial configuration into the goal configuration, as illustrated in Fig. 1.1. A solution to this problem is a sequence of moves leading from the initial configuration to the goal configuration, and an optimal solution is a solution having the smallest number of moves. Not all problems have solutions; for example, in Fig. 1.1, Problem 1 has many solutions while Problem 2 has no solution at all.
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We have written this book principally for users and practitioners of computer graphics. In particular, system designers, independent software vendors, graphics system implementers, and application program developers need to understand the basic standards being put in place at the so-called Virtual Device Interface and how they relate to other industry standards, both formal and de facto. Secondarily, the book has been targetted at technical managers and advanced students who need some understanding of the graphics standards and how they fit together, along with a good overview of the Computer Graphics Interface (CGI) proposal and Computer Graphics Metafile (CGM) standard in particular. Part I, Chapters 1,2, and 3; Part II, Chapters 10 and 11; Part III, Chapters 15, 16, and 17; and some of the Appendices will be of special interest. Finally, these same sections will interest users in government and industry who are responsible for selecting, buying and installing commercial implementations of the standards. The CGM is already a US Federal Information Processing Standard (FIPS 126), and we expect the same status for the CGI when its development is completed and it receives formal approval by the standards-making bodies.
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Automation is nothing new to industry. It has a long tradition on the factory floor, where its constant objective has been to increase the productivity of manufacturing processes. Only with the advent of computers could the focus of automation widen to include administrative and information-handling tasks. More recently, automation has been extended to the more intellectual tasks of production planning and control, material and resource planning, engineering design, and quality control. New challenges arise in the form of flexible manu facturing, assembly automation, and automated floor vehicles, to name just a few. The sheer complexity of the problems as well as the state of the art has led scientists and engineers to concentrate on issues that could easily be isolated. For example, it was much simpler to build CAD systems whose sole objective was to ease the task of drawing, rather than to worry at the same time about how the design results could be interfaced with the manufacturing or assembly processes. It was less problematic to gather statistics from quality control and to print reports than to react immediately to first hints of irregularities by inter facing with the designers or manufacturing control, or, even better, by auto matically diagnosing the causes from the design and planning data. A heav- though perhaps unavoidable - price must today be paid whenever one tries to assemble these isolated solutions into a larger, integrated system.
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TO COMPUTER GRAPHICS BASED ONGKS Part I gives an introduction to basic concepts of computer graph ics and to the principles and concepts of GKS. The aims of this part are twofold: to provide the beginner with an overview of the terminology and concepts of computer graphics, based on GKS, and to give the computer graphics expert an introduc tion to the GKS standard. In the early chapters of this part, the main areas of computer graphics, the various classes of com puter graphics users, the interfaces of GKS and its underlying design concepts are discussed and important terms are defined. The later chapters give an informal introduction to the main concepts of GKS and their interrelationships: output, attributes, coordinate systems, transformations, input, segments, metafile, state lists, and error handling. This introduction to the GKS framework will prepare the ground for the detailed description of 2D GKS functions in Part III and the 3D extensions to GKS in Part IV. 1 WHAT IS COMPUTER GRAPHICS? 1. 1 Defmition of Computer Graphics The Data Processing Vocabulary of the International Organization for Stan dardization (ISO) [ISO 84] defines Computer Graphics as follows: "Methods and techniques for converting data to and from a graphic display via computer. " This definition refers to three basic components of any computer graphics system - namely "data", "computer", and "display".
Computation of Language
An Essay on Syntax, Semantics and Pragmatics in Natural Man-Machine Communication
Häftad, Engelska, 2014
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The study of linguistics has been forever changed by the advent of the computer. Not only does the machine permit the processing of enormous quantities of text thereby securing a better empirical foundation for conclusions-but also, since it is a modelling device, the machine allows the implementation of theories of grammar and other kinds of language processing. Models can have very unexpected properties both good and bad-and it is only through extensive tests that the value of a model can be properly assessed. The computer revolution has been going on for many years, and its importance for linguistics was recognized early on, but the more recent spread of personal workstations has made it a reality that can no longer be ignored by anyone in the subject. The present essay, in particular, could never have been written without the aid of the computer. I know personally from conversations and consultations with the author over many months how the book has changed. If he did not have at his command a powerful typesetting program, he would not have been able to see how his writing looked and exactly how it had to be revised and amplified. Even more significant for the evolution of the linguistic theory is the easy testing of examples made possible by the implementation of the parser and the computer-held lexicon. Indeed, the rule set and lexicon grew substantially after the successes of the early implementations created the desire to incorporate more linguistic phenomena.
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"Kind of Cl'Ude ~ but it UJorks~ boy~ it UJOrksl" Alan Ner. ueH to Herb Simon~ C1rl'istmas 1955 In 1954 a computer program produced what appears to be the first computer generated mathematical proof: Written by M. Davis at the Institute of Advanced Studies, USA, it proved a number theoretic theorem in Presburger Arithmetic. Christmas 1955 heralded a computer program which generated the first proofs of some propositions of Principia Mathematica, developed by A. Newell, J. Shaw, and H. Simon at RAND Corporation, USA. In Sweden, H. Prawitz, D. Prawitz, and N. Voghera produced the first general program for the full first order predicate calculus to prove mathematical theorems; their computer proofs were obtained around 1957 and 1958, about the same time that H. Gelernter finished a computer program to prove simple high school geometry theorems. Since the field of computational logic (or automated theorem proving) is emerging from the ivory tower of academic research into real world applications, asserting also a definite place in many university curricula, we feel the time has come to examine and evaluate its history. The article by Martin Davis in the first of this series of volumes traces the most influential ideas back to the 'prehistory' of early logical thought showing how these ideas influenced the underlying concepts of most early automatic theorem proving programs.
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"Kind of crude, but it works, boy, it works!" AZan NeweZZ to Herb Simon, Christmas 1955 In 1954 a computer program produced what appears to be the first computer generated mathematical proof: Written by M. Davis at the Institute of Advanced Studies, USA, it proved a number theoretic theorem in Presburger Arithmetic. Christmas 1955 heralded a computer program which generated the first proofs of some propositions of Principia Mathematica, developed by A. Newell, J. Shaw, and H. Simon at RAND Corporation, USA. In Sweden, H. Prawitz, D. Prawitz, and N. Voghera produced the first general program for the full first order predicate calculus to prove mathematical theorems; their computer proofs were obtained around 1957 and 1958, about the same time that H. Gelernter finished a computer program to prove simple high school geometry theorems. Since the field of computational logic (or automated theorem proving) is emerging from the ivory tower of academic research into real world applications, asserting also a definite place in many university curricula, we feel the time has corne to examine and evaluate its history. The article by Martin Davis in the first of this series of volumes traces the most influential ideas back to the 'prehistory' of early logical thought showing how these ideas influenced the underlying concepts of most early automatic theorem proving programs.
Design of Interpreters, Compilers, and Editors for Augmented Transition Networks
Häftad, Engelska, 2011
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Augmented Transition Network Grammars are at present the most widely used method for analyzing natural languages. Despite the increasing po pularity of this method, however, no extensive papers on ATN-Grammars have been presented which would be accessible to a larger number of per sons engaged in the problem from both the theoretical and practical points of view. Augmented Transition Networks (ATN) are derived from state automata. Like a finite state automaton, an ATN consists of a collection of la beled states and arcs, a distinguished start state and a set of distin guished final states. States are connected with each other by arcs crea ting a directed graph or net. The label on an arc indicates a terminal symbol (word) or the type of words which must occur in an input stream to allow the transition to the next state. It is said that a sequence of words (or sentence) is accepted by such a net if there exists a se quence of arcs (usually called a path), connecting the start state with a final state, which can be followed to the sentence. The finite state automaton is then enriched by several facilities which increase its computational power. The most important of them permits some arcs to be labeled by nonterminal rather than terminal symbols. This means that the transition through such an arc is actually the re cursive application of the net beginning with a pointed state.
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This book contains the reports of selected projects involving natural language commu nication with pictorial information systems. More than just a record of research results, however, it presents concrete applications to the solution of a wide variety of problems. The authors are all prominent figures in the field whose authoritative contributions help ensure its continued expansion in both size and significance. Y. C. Lee and K S. Fu (Purdue University, USA) survey picture query languages which form an interface between the pictorial database system and the user and support infor mation retrieval, data entry and manipulation, data analysis and output generation. They include explicit picture query languages that augment alphanumeric data query langua ges as well as languages and command sets which are implicitly embedded in a pictorial information system but perform similar functions. It is worth mentioning that some forms of query languages can be transformed from a given set of natural language senten ces by using ATN (Augmented Transition Networks), which consequently allows for na turallanguage communication with information system.
Product Data Interfaces in CAD/CAM Applications
Design, Implementation and Experiences
Häftad, Engelska, 2011
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Interest in product data exchange and interfaces in the CAD/CAM area is steadi ly growing. The rapidly increasing graphics applications in engineering and sci ence has led to a great variety of heterogeneous hardware and software products. This has become a major obstacle in the progress of systems integration. To improve this situation CAD/CAM users have called for specification and imple mentation of standardized product data interfaces. These needs resulted in the definition of preliminary standards in this area. Since 1975 activities have been concentrated on developing standards for three major areas: - computer graphics, - sculptured surfaces, and - data exchange for engineering drawings. The Graphical Kernel System (GKS) has been accepted as an international standard for graphics programming in 1984, Y14.26M (IGES) was adopted as an American Standard in 1981 and the VDA Surface Interface (VDAFS) has been accepted by the German National Standardization Institute (DIN NAM 96.4). Although considerable progress has been achieved, the complexity of the subject and the dynamics of the CAD/CAM-development still calls for more generality and compatibility of the interfaces. This has resulted in an inter national discussion on further improvements of the standards. The major goal of this book is to bring together the different views and experiences in industry and university in the area of Product Data Interfaces, thereby contributing to the ongoing work in improving the state of the art.
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The purpose of computer vision is to make computers capable of understanding environments from visual information. Computer vision has been an interesting theme in the field of artificial intelligence. It involves a variety of intelligent information processing: both pattern processing for extraction of meaningful symbols from visual information and symbol processing for determining what the symbols represent. The term "3D computer vision" is used if visual information has to be interpreted as three-dimensional scenes. 3D computer vision is more challenging because objects are seen from limited directions and some objects are occluded by others. In 1980, the author wrote a book "Computer Vision" in Japanese to introduce an interesting new approach to visual information processing developed so far. Since then computer vision has made remarkable progress: various rangefinders have become available, new methods have been developed to obtain 3D informa tion, knowledge representation frameworks have been proposed, geometric models which were developed in CAD/CAM have been used for computer vision, and so on. The progress in computer vision technology has made it possible to understand more complex 3 D scenes. There is an increasing demand for 3D computer vision. In factories, for example, automatic assembly and inspection can be realized with fewer con straints than conventional ones which employ two-dimensional computer vision.
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In recent years, machine learning has emerged as a significant area of research in artificial intelligence and cognitive science. At present, research in the field is being intensified from both the point of view of theory and of implementation, and the results are being introduced in practice. Machine learning has recently become the subject of interest of many young and talented scientists whose bold ideas have greatly contributed to the broadening of knowledge in this rapidly developing field of science. This situation has manifested itself in an increasing number of valuable contributions to scientific journals. However, such papers are necessarily compact descriptions of research problems. Computational Models of Learning supplements these contributions and is a collection of more extensive essays. These essays provide the reader with an increased knowledge of carefully selected problems of machine learning.
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Previous works on industrial robots dealt with "programming" and "programming languages" only in passing; no comparison was made between characteristics of the individual programming lan guages. This book, therefore, gives a detailed account of industrial robot programming and its environment. Mter introducing basic concepts special attention is paid to the language constructs relevant to robot programming. The features of various elements of the languages ex amined are compared. The languages are based on the following concepts: SRL - high-level programming language based on AL with PASCAL elements (University of Karlsruhe, F. R G. ) PASRO - integrated into PASCAL, based on the geometrical data types of SRL (I. I. -BIOMATIC Informatics Institute, Freiburg, F. RG. ) AL - derived from the high-level programming language ALGOL (Stanford University, U. S. A. , and University of Karls ruhe, F. RG. ) AML - high-level programming language, influenced by PL/1 (IBM, U. S. A. ) VAL - language specifically developed for robots (Unimation, U. S. A. ) HELP - mixture of high-level language elements and robot l- guage elements and real-time processing (DEA, Italy) SIGLA - a simple machine language (Olivetti, Italy) ROBEX - based on NC programming (Technical College (RWTH), Aachen, F. RG. ) RAIL - high-level programming language for industrial robots with elements for graphic processing (Automatix, U. S. A. ) IRDATA - general software interface between programming and robot controller (Association of German Engineers (VDI), F. R G.