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This study is part of the preparatory work needed for establishing a foundational comprehension of specific aspects related to the research goal, which is to investigate the multidimensional interplay of individual factors and context in shaping trust towards Artificial Intelligence Expert Systems. This study is primarily a validation study in a representative German sample. It aims to validate a generally satisfying description of how an AIES should be described such that people can make an informed decision on whether they would want to use that system or not. Initially, a set of descriptive elements was introduced and exploratively analyzed in a predecessor study (https://doi.org/10.17605/OSF.IO/YQZGK). The descriptive elements identified as 'most essential' components of a comprehensive yet concise description are presented herein. It further aims to replicate and confirm the factor structure of a translated propensity to trust scale by Frazier et al. 2013. Additionally, it identifies people's risk and trust perceptions in five different contexts (medicine, psychotherapy, law, education, and finance).

Artificial intelligence (AI) is the field of scientific inquiry concerned with designing machine systems that can simulate human mental processes. The field draws upon theoretical constructs from a wide variety of disciplines, including mathematics, psychology, linguistics, neurophysiology, computer science, and electronic engineering. Some of the most promising developments to come out of recent AI research are "expert" systems or computer programs that simulate the problem-solving techniques of human experts in a particular domain. This paper reviews contemporary work in expert systems. It includes: (1) a brief history of AI research; (2) an overview of major lines of inquiry in the field, considering pattern recognition, robotics, and problem-solving; (3) a detailed discussion of the structure, design, and limitations of expert systems; and (4) a discussion of the role that expert systems might play in education. Two appendices are included. The first presents an example of interaction with an expert system; the second lists major systems that are currently in use or under development in the categories of bioengineering, chemistry, computer hardware, computer software, education, engineering, general purpose systems and artificial intelligence utilities, law, manufacturing and industry, mathematics, medicine, the military, and resource exploration. (JN)

Artificial intelligence (AI) is the field of scientific inquiry concerned with designing machine systems that can simulate human mental processes. The field draws upon theoretical constructs from a wide variety of disciplines, including mathematics, psychology, linguistics, neurophysiology, computer science, and electronic engineering. Some of the most promising developments to come out of recent AI research are "expert" systems or computer programs that simulate the problem-solving techniques of human experts in a particular domain. This paper reviews contemporary work in expert systems. It includes: (1) a brief history of AI research; (2) an overview of major lines of inquiry in the field, considering pattern recognition, robotics, and problem-solving; (3) a detailed discussion of the structure, design, and limitations of expert systems; and (4) a discussion of the role that expert systems might play in education. Two appendices are included. The first presents an example of interaction with an expert system; the second lists major systems that are currently in use or under development in the categories of bioengineering, chemistry, computer hardware, computer software, education, engineering, general purpose systems and artificial intelligence utilities, law, manufacturing and industry, mathematics, medicine, the military, and resource exploration. (JN)

Includes bibliographical references and index

Includes bibliographical references and index

Includes bibliographical references and index

XIII, 242 Seiten

XIII, 242 Seiten

XIII, 242 Seiten

xxiv,424p. : 24 cm

xxiv,424p. : 24 cm

Zimbabwe experienced a deteriorating economic and social environment since 2000 that was caused by illegal economic sanctions imposed by the Western countries. This resulted in a deep economic and social crisis characterized by a hyperinflationary environment, industrial capacity utilization of below 10% and an overall cumulative Gross Domestic Product (GDP) decline of 50% by 2008. To guide national development for the next five years, the Government has crafted a new economic blueprint known as the Zimbabwe Agenda for Sustainable Socio-Economic Transformation (Zim Asset). 

Zimbabwe experienced a deteriorating economic and social environment since 2000 that was caused by illegal economic sanctions imposed by the Western countries. This resulted in a deep economic and social crisis characterized by a hyperinflationary environment, industrial capacity utilization of below 10% and an overall cumulative Gross Domestic Product (GDP) decline of 50% by 2008. To guide national development for the next five years, the Government has crafted a new economic blueprint known as the Zimbabwe Agenda for Sustainable Socio-Economic Transformation (Zim Asset). 

Zimbabwe experienced a deteriorating economic and social environment since 2000 that was caused by illegal economic sanctions imposed by the Western countries. This resulted in a deep economic and social crisis characterized by a hyperinflationary environment, industrial capacity utilization of below 10% and an overall cumulative Gross Domestic Product (GDP) decline of 50% by 2008. To guide national development for the next five years, the Government has crafted a new economic blueprint known as the Zimbabwe Agenda for Sustainable Socio-Economic Transformation (Zim Asset). 

Zimbabwe experienced a deteriorating economic and social environment since 2000 that was caused by illegal economic sanctions imposed by the Western countries. This resulted in a deep economic and social crisis characterized by a hyperinflationary environment, industrial capacity utilization of below 10% and an overall cumulative Gross Domestic Product (GDP) decline of 50% by 2008. To guide national development for the next five years, the Government has crafted a new economic blueprint known as the Zimbabwe Agenda for Sustainable Socio-Economic Transformation (Zim Asset). 

Systems such as those that play games, diagnose engine problems, or organize cargo loads in ships are all examples of artificial intelligence. The sub-discipline of expert systems deals with computerized imitation of the reasoning of judgment process of human experts. CECOM's expert system for tactical planning draws its tactical expertise from the US Army War College students that comprise study group. Computer scientists who have a long-term commitment to the CECOM project work with the study group experts to extract and understand what rules, guidelines, or thought processes the group uses to generate a tactical plan for a Corps operation. The computer scientist takes these lists of information and converts them into computer knowledge which eventually becomes rules that will govern program output. In the heuristic environment of tactical planning, it would not be unreasonable to expect the finished expert system to contain between 20 and 50,000 such rules. The multi-year approach to the project is driven home by the recognition that a hand-crafted expert system might have 20 rules after the first year of effort. By working with CECOM's knowledge engineers, participating in numerous group sessions, going on TDY trips, and reading extensively, study group members developed an appreciation for some of the difficulties and opportunities associated with the use of artificial intelligence in its various military applications.

Systems such as those that play games, diagnose engine problems, or organize cargo loads in ships are all examples of artificial intelligence. The sub-discipline of expert systems deals with computerized imitation of the reasoning of judgment process of human experts. CECOM's expert system for tactical planning draws its tactical expertise from the US Army War College students that comprise study group. Computer scientists who have a long-term commitment to the CECOM project work with the study group experts to extract and understand what rules, guidelines, or thought processes the group uses to generate a tactical plan for a Corps operation. The computer scientist takes these lists of information and converts them into computer knowledge which eventually becomes rules that will govern program output. In the heuristic environment of tactical planning, it would not be unreasonable to expect the finished expert system to contain between 20 and 50,000 such rules. The multi-year approach to the project is driven home by the recognition that a hand-crafted expert system might have 20 rules after the first year of effort. By working with CECOM's knowledge engineers, participating in numerous group sessions, going on TDY trips, and reading extensively, study group members developed an appreciation for some of the difficulties and opportunities associated with the use of artificial intelligence in its various military applications.

Systems such as those that play games, diagnose engine problems, or organize cargo loads in ships are all examples of artificial intelligence. The sub-discipline of expert systems deals with computerized imitation of the reasoning of judgment process of human experts. CECOM's expert system for tactical planning draws its tactical expertise from the US Army War College students that comprise study group. Computer scientists who have a long-term commitment to the CECOM project work with the study group experts to extract and understand what rules, guidelines, or thought processes the group uses to generate a tactical plan for a Corps operation. The computer scientist takes these lists of information and converts them into computer knowledge which eventually becomes rules that will govern program output. In the heuristic environment of tactical planning, it would not be unreasonable to expect the finished expert system to contain between 20 and 50,000 such rules. The multi-year approach to the project is driven home by the recognition that a hand-crafted expert system might have 20 rules after the first year of effort. By working with CECOM's knowledge engineers, participating in numerous group sessions, going on TDY trips, and reading extensively, study group members developed an appreciation for some of the difficulties and opportunities associated with the use of artificial intelligence in its various military applications.

Systems such as those that play games, diagnose engine problems, or organize cargo loads in ships are all examples of artificial intelligence. The sub-discipline of expert systems deals with computerized imitation of the reasoning of judgment process of human experts. CECOM's expert system for tactical planning draws its tactical expertise from the US Army War College students that comprise study group. Computer scientists who have a long-term commitment to the CECOM project work with the study group experts to extract and understand what rules, guidelines, or thought processes the group uses to generate a tactical plan for a Corps operation. The computer scientist takes these lists of information and converts them into computer knowledge which eventually becomes rules that will govern program output. In the heuristic environment of tactical planning, it would not be unreasonable to expect the finished expert system to contain between 20 and 50,000 such rules. The multi-year approach to the project is driven home by the recognition that a hand-crafted expert system might have 20 rules after the first year of effort. By working with CECOM's knowledge engineers, participating in numerous group sessions, going on TDY trips, and reading extensively, study group members developed an appreciation for some of the difficulties and opportunities associated with the use of artificial intelligence in its various military applications.

Systems such as those that play games, diagnose engine problems, or organize cargo loads in ships are all examples of artificial intelligence. The sub-discipline of expert systems deals with computerized imitation of the reasoning of judgment process of human experts. CECOM's expert system for tactical planning draws its tactical expertise from the US Army War College students that comprise study group. Computer scientists who have a long-term commitment to the CECOM project work with the study group experts to extract and understand what rules, guidelines, or thought processes the group uses to generate a tactical plan for a Corps operation. The computer scientist takes these lists of information and converts them into computer knowledge which eventually becomes rules that will govern program output. In the heuristic environment of tactical planning, it would not be unreasonable to expect the finished expert system to contain between 20 and 50,000 such rules. The multi-year approach to the project is driven home by the recognition that a hand-crafted expert system might have 20 rules after the first year of effort. By working with CECOM's knowledge engineers, participating in numerous group sessions, going on TDY trips, and reading extensively, study group members developed an appreciation for some of the difficulties and opportunities associated with the use of artificial intelligence in its various military applications.

This study is an analysis of the evolution of artificial intelligence and expert computer systems in the U.S. Army and the role the Army should play in the future evolution of these technologies. This study investigates the Army's approach to the development and use of these computer systems. It will assess whether the Army should play a leadership or a follower role in the development of these systems. The Army's decision to either lead or follow in these technologies will have significant effects on the limited resources of tomorrows smaller and less resourced force. This study will examine these issues given the trend in reduced fiscal resources and personnel. The civilian sector's development and use of these systems are evaluated to determine benefits to the Army through the use of these systems. The adaptability of these systems to various Army requirements are evaluated as are the near and far term costs of these systems. This study concludes that the U.S. Army should play a follower role in the future evolution of both expert computer systems and artificial intelligence. The Army should exploit current technologies and help guide the civilian community in the research and development of military applications.

This study is an analysis of the evolution of artificial intelligence and expert computer systems in the U.S. Army and the role the Army should play in the future evolution of these technologies. This study investigates the Army's approach to the development and use of these computer systems. It will assess whether the Army should play a leadership or a follower role in the development of these systems. The Army's decision to either lead or follow in these technologies will have significant effects on the limited resources of tomorrows smaller and less resourced force. This study will examine these issues given the trend in reduced fiscal resources and personnel. The civilian sector's development and use of these systems are evaluated to determine benefits to the Army through the use of these systems. The adaptability of these systems to various Army requirements are evaluated as are the near and far term costs of these systems. This study concludes that the U.S. Army should play a follower role in the future evolution of both expert computer systems and artificial intelligence. The Army should exploit current technologies and help guide the civilian community in the research and development of military applications.

This study is an analysis of the evolution of artificial intelligence and expert computer systems in the U.S. Army and the role the Army should play in the future evolution of these technologies. This study investigates the Army's approach to the development and use of these computer systems. It will assess whether the Army should play a leadership or a follower role in the development of these systems. The Army's decision to either lead or follow in these technologies will have significant effects on the limited resources of tomorrows smaller and less resourced force. This study will examine these issues given the trend in reduced fiscal resources and personnel. The civilian sector's development and use of these systems are evaluated to determine benefits to the Army through the use of these systems. The adaptability of these systems to various Army requirements are evaluated as are the near and far term costs of these systems. This study concludes that the U.S. Army should play a follower role in the future evolution of both expert computer systems and artificial intelligence. The Army should exploit current technologies and help guide the civilian community in the research and development of military applications.

This study is an analysis of the evolution of artificial intelligence and expert computer systems in the U.S. Army and the role the Army should play in the future evolution of these technologies. This study investigates the Army's approach to the development and use of these computer systems. It will assess whether the Army should play a leadership or a follower role in the development of these systems. The Army's decision to either lead or follow in these technologies will have significant effects on the limited resources of tomorrows smaller and less resourced force. This study will examine these issues given the trend in reduced fiscal resources and personnel. The civilian sector's development and use of these systems are evaluated to determine benefits to the Army through the use of these systems. The adaptability of these systems to various Army requirements are evaluated as are the near and far term costs of these systems. This study concludes that the U.S. Army should play a follower role in the future evolution of both expert computer systems and artificial intelligence. The Army should exploit current technologies and help guide the civilian community in the research and development of military applications.

This study is an analysis of the evolution of artificial intelligence and expert computer systems in the U.S. Army and the role the Army should play in the future evolution of these technologies. This study investigates the Army's approach to the development and use of these computer systems. It will assess whether the Army should play a leadership or a follower role in the development of these systems. The Army's decision to either lead or follow in these technologies will have significant effects on the limited resources of tomorrows smaller and less resourced force. This study will examine these issues given the trend in reduced fiscal resources and personnel. The civilian sector's development and use of these systems are evaluated to determine benefits to the Army through the use of these systems. The adaptability of these systems to various Army requirements are evaluated as are the near and far term costs of these systems. This study concludes that the U.S. Army should play a follower role in the future evolution of both expert computer systems and artificial intelligence. The Army should exploit current technologies and help guide the civilian community in the research and development of military applications.

This study is an analysis of the evolution of artificial intelligence and expert computer systems in the U.S. Army and the role the Army should play in the future evolution of these technologies. This study investigates the Army's approach to the development and use of these computer systems. It will assess whether the Army should play a leadership or a follower role in the development of these systems. The Army's decision to either lead or follow in these technologies will have significant effects on the limited resources of tomorrows smaller and less resourced force. This study will examine these issues given the trend in reduced fiscal resources and personnel. The civilian sector's development and use of these systems are evaluated to determine benefits to the Army through the use of these systems. The adaptability of these systems to various Army requirements are evaluated as are the near and far term costs of these systems. This study concludes that the U.S. Army should play a follower role in the future evolution of both expert computer systems and artificial intelligence. The Army should exploit current technologies and help guide the civilian community in the research and development of military applications.

This study is an analysis of the evolution of artificial intelligence and expert computer systems in the U.S. Army and the role the Army should play in the future evolution of these technologies. This study investigates the Army's approach to the development and use of these computer systems. It will assess whether the Army should play a leadership or a follower role in the development of these systems. The Army's decision to either lead or follow in these technologies will have significant effects on the limited resources of tomorrows smaller and less resourced force. This study will examine these issues given the trend in reduced fiscal resources and personnel. The civilian sector's development and use of these systems are evaluated to determine benefits to the Army through the use of these systems. The adaptability of these systems to various Army requirements are evaluated as are the near and far term costs of these systems. This study concludes that the U.S. Army should play a follower role in the future evolution of both expert computer systems and artificial intelligence. The Army should exploit current technologies and help guide the civilian community in the research and development of military applications.

This is a collection of papers, presentations and discussions at a conference on dealing with uncertainty in artificial intelligence and expert systems. Three different approaches were examined, namely (1) The use of belief functions, (2) fussy set logic, and (3) probability. A case study example of a probabilistic approach for expert systems in medicine was presented.

This is a collection of papers, presentations and discussions at a conference on dealing with uncertainty in artificial intelligence and expert systems. Three different approaches were examined, namely (1) The use of belief functions, (2) fussy set logic, and (3) probability. A case study example of a probabilistic approach for expert systems in medicine was presented.

This is a collection of papers, presentations and discussions at a conference on dealing with uncertainty in artificial intelligence and expert systems. Three different approaches were examined, namely (1) The use of belief functions, (2) fussy set logic, and (3) probability. A case study example of a probabilistic approach for expert systems in medicine was presented.

A review of the literature in the field of artificial intelligence was performed to identify research and development efforts in industry, academia, and government laboratories that may be related (or relatable) to the cockpit management function in tomorrow's aircraft. Individual chapters address the following topics: Chapter 1 - An Introduction to Artificial Intelligence and Expert Systems; Chapter 2 - Artificial Intelligence Development Applications in DARPA, DOD, and NASA; Chapter 3 - State-of-the-Art Review and Projection of Future Expert System Developments; Chapter 4 - Human Factors Research in Artificial Intelligence and Expert Systems; Chapter 5 - Image Understanding; Chapter 6 - Natural Language Processing/Understanding, and; Chapter 7 - Summary Comments on the Development and Application of Artificial Intelligence and Expert Systems. Separate bibliographies are provided at the end of each chapter to assist the reader in identifying specific literature of interest. A glossary of abbreviations, acronyms, and special terms used in the context of this report is also provided.

CONTENTS: Adaptive architectures; Case-based reasonong; Computer aided manufacturing; Diagnosis; Fuzzy logic and control; Image; Knowledge acquisition; Knowledge based systems; Model based- reasoning; Modelling; Software engineering; Invited presentation. (KAR) p. 3

CONTENTS: Adaptive architectures; Case-based reasonong; Computer aided manufacturing; Diagnosis; Fuzzy logic and control; Image; Knowledge acquisition; Knowledge based systems; Model based- reasoning; Modelling; Software engineering; Invited presentation. (KAR) p. 3

U-SA1__Artificial Intelligence and Expert Systems

This report consists of the syllabus, instructor lesson guides, viewgraphs, and bibliography for a course of instruction taught by the author as an elective at The National Defense University during the spring semester of 1986. The course is designed to acquaint senior level decision makers with the rapidly advancing field of artificial intelligence and the first practical use of this new technology commonly know as expert systems. The course consists of lectures, demonstrations, and guest speakers to give the senior executive a feel for the state-of-the-art in computer technology as well as to demonstrate potential applications of this new tool. It also provides the students an opportunity to develop a small expert system using a shell or tool on a microcomputer.