During the past two years, the Dempster-Shafer theory of evidence has attracted considerable attention within the AI community as a promising method of dealing with uncertainty in expert systems. As presented in the literature, the theory is hard to master. In a simple approach that is outlined in this paper, the Dempster-Shafer theory is viewed in the context of relational databases as the application of familiar retrieval techniques to second-order relations in first normal form. The relational viewpoint clarifies some of the controversial issues in the Dempster-Shafer theory and facilities its use in AI-oriented applications.

The third approach left the technology codes untouched and built a procedural program that initiated separate, independent processes consisting of the technology codes communicating through a common database. This was better because the technology organizations continued to maintain technical and managerial control over their codes. The rigid procedural integration program was still unacceptably costly to modify, requiring a flow time of approximately six weeks. However, it did provide a prototype and baseline for the knowledge system.

The possibility of constructing a personal AI raises many ethical and religious questions that have been dealt with seriously only by imaginative works of fiction; they have largely been ignored by technical experts and by philosophical and theological ethicists. Arguing that a personal AI is possible in principle, and that its accomplishments could be adjudicated by the Turing Test, the article suggests some of the moral issues involved in AI experimentation by comparing them to issues in medical experimentation. Finally, the article asks questions about the capacities and possibilities of such an artifact for making moral decisions. It is suggested that much a priori ethical thinking is necessary and that, that such a project cannot only stimulate our moral imaginations, but can also tell us much about our moral thinking and pedagogy, whether or not it is ever accomplished in fact.

THE AI MAGAZINE Summer, 1986 55 building one of the first stored-program digital computers, AI also had its share of controversy, however, at Rand the JOHNNIAC (see Figure 1) (Gruenberger, 1968);l and elsewhere. Given its quick rise to popularity and its George Dantzig and his associates were inventing linear ambitious predictions (Simon & Newell, 1958), AI soon programming (Dantzig, 1963); Les Ford and Ray Fulkerson had its critics, and one of the most prominent, Hubert were developing techniques for network flow analysis Dreyfus, published his famous critique of AI (Dreyfus, (Ford & Fulkerson, 1962); Richard Bellman was developing 1965) while he was consulting at Rand. In addition, the his ideas on dynamic programming (Bellman, 1953); early promise of automatic machine translation of text Herman Kahn was advancing techniques for Monte Carlo from one language to another (the emphasis at Rand was simulation (Kahn, 1955); Lloyd Shapley was revolutionizing on translation from Russian to English) produced only game theory (Shapley, 1951-1960); Stephen Kleene was modest systems, and the goal of fully automated machine advancing our understanding of finite automata (Kleene, translation was abandoned in the early 1960s.

Letters to the Editor

Review of Artificial Intelligence and Robotics: Five Overviews

Review of Artificial Intelligence: The Very Idea

Review of Heuristics: Intelligent Search Strategies for Computer Problem Solving

The Advanced Computational Methods Center (ACMC) established at the University of Georgia in 1984, supports several research projects in artificial intelligence. The primary goal of AI research at ACMC is the design and installation of a logic-programming environment with advanced natural language processing and knowledge-acquisition capabilities on the university's highly parallel CYBERPLUS system from Control Data Corporation.

This article presents a summary of past and current artificial intelligence research within the Computer Science Department at East Texas State University (ETSU). The Computer Science Department at ETSU offers a master of science degree with an emphasis in artificial intelligence. AI research, both past and present, has been funded by a grant from E-Systems, Greenville Division. Other computing facilities available for artificial intelligence research are four workstations, each providing up to 20 users with LISP and PROLOG interpreters.