This volume contains papers in the areas of artificial intelligence, expert systems, symbolic computing and applications to scientific computing. Together, they provide an excellent overview of the dynamic state of these closely related fields. They reveal a future where scientific computation will increasingly involve symbolic and artificial intelligence tools as these software systems become more sophisticated; also a future where systems of computational science and engineering will be problem solving environments created with components from numerical analysis, computational geometry, symbolic computing and artificial intelligence.

While expert systems technology originated in the United States, its development has become an international concern. Since the start of the DENDRAL project at Stanford University over 15 years ago, with its objective of problem-solving via the automation of actual human expert knowledge, significant expert systems projects have been completed in countries rang ing from Japan to France, Spain to China. This book presents a sample of five such projects, along with four substantial reports of mature studies from North American researchers. Two important issues of expert system design permeate the papers in this volume. The first concerns the incorporation of substantial numeric knowledge into a system. This has become a significant focus of work as researchers have sought to apply expert systems tech nology to complex, real-world domains already subject to statistical or algebraic description (and handled well at some level in numeric terms). A second prominent issue is that of representing control knowledge in a manner which is both explicit, and thus available for inspection, and compatible with the semantics of the problem domain.

What Is Symbolic Artificial Intelligence In the field of artificial intelligence, the term "symbolic artificial intelligence" refers to the collection of all methods in artificial intelligence research that are based on high-level symbolic (human-readable) representations of issues, logic, and search. In other words, symbolic artificial intelligence is the name for the collection of all methods in artificial intelligence research. Symbolic AI created applications such as knowledge-based systems, symbolic mathematics, automated theorem provers, ontologies, the semantic web, and automated planning and scheduling systems. It utilized techniques such as logic programming, production rules, and semantic nets and frames. The paradigm of symbolic artificial intelligence led to the development of important ideas in the fields of search, symbolic programming languages, agents, multi-agent systems, the semantic web, as well as the benefits and drawbacks of formal knowledge and reasoning systems. How You Will Benefit (I) Insights, and validations about the following topics: Chapter 1: Symbolic Artificial Intelligence Chapter 2: Artificial Intelligence Chapter 3: Expert System Chapter 4: Knowledge Representation and Reasoning Chapter 5: Neats and Scruffies Chapter 6: Dendral Chapter 7: Computational Cognition Chapter 8: Physical Symbol System Chapter 9: History of Artificial Intelligence Chapter 10: Hybrid Intelligent System (II) Answering the public top questions about symbolic artificial intelligence. (III) Real world examples for the usage of symbolic artificial intelligence in many fields. (IV) 17 appendices to explain, briefly, 266 emerging technologies in each industry to have 360-degree full understanding of symbolic artificial intelligence' technologies. Who This Book Is For Professionals, undergraduate and graduate students, enthusiasts, hobbyists, and those who want to go beyond basic knowledge or information for any kind of symbolic artificial intelligence.

This book constitutes the thoroughly refereed post-proceedings of the International Conference on Artificial Intelligence and Symbolic Computation, AISC 2000, held in Madrid, Spain in July 2000. The 17 revised full papers presented together with three invited papers were carefully reviewed and revised for inclusion in the book. Among the topics addressed are automated theorem proving, logical reasoning, mathematical modeling of multi-agent systems, expert systems and machine learning, computational mathematics, engineering, and industrial applications.

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 30 pointer into the literature. Thus the AI community will have access to 30 common, extensional definition of the field, which will: promote 30 common terminology, discourage the reinvention of w heels, and act as 30 clearing house for ideas and software. The catalogue is 30 reference work providing 30 quick guide to the AI tools ava.ilable for different jobs. It is not intended to be 30 textbook like the Artificial Intelligence Handbook. It, intentiona11y, only provides 30 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-DoI, IKBS, Architecture Study. It has now been adopted by the UK Alvey Programme and is both kept as an on-line document undergoing constant revision and refinement and published as 30 paperback by Springer-Verlag. Springer-Verlag have agreed to reprint the Catalogue at frequent intervals in order to keep it up to date.