Towards a general theory of action and time
Artificial Intelligence
Programming in Prolog (2nd ed.)
Programming in Prolog (2nd ed.)
Programming expert systems in OPS5: an introduction to rule-based programming
Programming expert systems in OPS5: an introduction to rule-based programming
Machine learning an artificial intelligence approach volume II
Machine learning an artificial intelligence approach volume II
Common fallacies about expert systems
ACM SIGCAS Computers and Society
The rise of the expert company
The rise of the expert company
The Hearsay-II Speech-Understanding System: Integrating Knowledge to Resolve Uncertainty
ACM Computing Surveys (CSUR)
Computer science as empirical inquiry: symbols and search
Communications of the ACM
A review of barriers to expert system diffusion
SIGBDP '90 Proceedings of the 1990 ACM SIGBDP conference on Trends and directions in expert systems
The Organization and Performance of a TREAT-Based Production System Compiler
IEEE Transactions on Knowledge and Data Engineering
Validating an expert system for financial statement planning
Journal of Management Information Systems - Special issue: Organizational impact of group support systems, expert systems, and executive information systems
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The author identifies major causes leading to ineffective application of artificial intelligence (AI). His views are based on personal observations made over ten years of building, deploying, and reviewing AI-based systems. The author attributes most failures to one or both of the following: misconceptions regarding the nature of AI technology, and poor management skills in acquiring, nurturing, and applying that technology. He sets forth core AI concepts and then examines and debunks some common misconceptions about expert systems, their construction, and their maintenance.