Government
Artificial Intelligence: A Rand Perspective
Klahr, Philip, Waterman, Donald A.
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.
Recent and Current Artificial Intelligence Research in the Department of Computer Science SUNY at Buffalo
Hardt, Shoshana L., Rapaport, William J.
The interpretation of images of postal mail pieces is The Vision Group the domain of this investigation. Our efforts have included It is becoming increasingly important for vision researchers the development of various operators for visual data processing in diverse fields to interact, and the Vision Group at SUNY and image segmentation. The invocation of these Buffalo was formed to facilitate that interaction Current routines and the interpretation of the information they return membership includes 25 faculty and 25 students from 10 is determined by a control structure that uses a variant departments (computer science, electrical and computer of relaxation combined with a rule-based methodology.
Artificial Intelligence Research and Applications at the NASA Johnson Space Center: Part One
Research and applications work in AI is being conducted by several groups at Johnson Space Center (JSC). These are primarily independent groups that interact with each other on an informal basis. In the Research and Engineering Directorate, these groups include (1) the Artificial Intelligence and Information Sciences Office, (2) the Simulation and Avionics Integration Division, (3) the Avionics Systems Division (ASD), and (4) the Tracking and Communications Division. In the Space Operations Directorate, these groups include (1) the Mission Planning and Analysis Division - Technology Development and Applications Branch, (2) the Spacecraft Software Division, and (3) the Systems Division-Systems Support Section. The first part of the article describes the AI work in Research and Engineering Directorate. The second part of the article, to be published in the Conference edition of the AI Magazine, describes the AI work in the Space Operations Directorate
KBEmacs: Where's the AI?
The Knowledge-Based Editor in Emacs (KBEmacs) is the current demonstration system implemented as part of the Programmer's Apprentice project. KBEmacs is capable of acting as a semiexpert assistant to a person who is writing a program, taking over some parts of the programming task. The abilities of KBEmacs stem directly from a few key AI ideas. However, in many ways KBEmacs does not appear to be an AI system, because its abilities are limited and because (like many applied AI systems) the AI ideas are buried in a large volume of code that has little relevance to AI. The primary goal of this article is to present the AI ideas behind KBEmacs. In addition, the construction of applied AI systems is discussed, in general, using the development of KBEmacs as a case history
CYC: Using Common Sense Knowledge to Overcome Brittleness and Knowledge Acquisition Bottlenecks
Lenat, Douglas B., Prakash, Mayank, Shepherd, Mary
The major limitations in building large software have always been (a) its brittleness when confronted by problems that were not foreseen by its builders, and (by the amount of manpower required. The recent history of expert systems, for example highlights how constricting the brittleness and knowledge acquisition bottlenecks are. Moreover, standard software methodology (e.g., working from a detailed "spec") has proven of little use in AI, a field which by definition tackles ill- structured problems. How can these bottlenecks be widened? Attractive, elegant answers have included machine learning, automatic programming, and natural language understanding. But decades of work on such systems have convinced us that each of these approaches has difficulty "scaling up" for want a substantial base of real world knowledge.
Artificial Intelligence at MITRE
The MITRE Corporation is a scientific and technical organization engaged in systems engineering activities, principally in support of the United States Air Force and other government agencies, and primarily in the field of information systems. MITRE is a special kind of engineering organizations. The corporation is a Federal Contract Research Center, a designation covering the handful of independent institutions that perform government sponsored research. It is an independent, nonprofit corporation designed and managed to provide long-term assistance to government agencies in planning, design, procurement, and testing of their information systems.
Review of "Report on the 1984 Distributed Artificial Intelligence Workshop
The fifth Distributed Artificial Intelligence Workshop was held at the Schlumberger-Doll Research Laboratory from October 14 to 17, 1984. It was attended by 20 participants from academic and industrial institutions. As in the past, this workshop was designed as an informal meeting. It included brief research reports from individual groups along with general discussion of questions of common interest. This report summarizes the general discussion and contains summaries of group presentations that have been contributed by individual speakers.
The History of Artificial Intelligence at Rutgers
The founding of a new college at Rutgers in 1969 became the occasion for building a strong computer science presence in the University. Livingston College thus provided the home for the newly organized Department of Computer Science (DCS) and for the beginning of computer science research at Rutgers.
Artificial Intelligence at MITRE
The MITRE Corporation is a scientific and technical an acronym for Knowledge-Based System. Subsequently, organization engaged in system engineering activities, Rome Air Development Center took over support of the principally in support of the United States Air Force and project and continues to fund part of our AI research effort. MITRE is a special kind of engineering MITRE's current research is summarized below. The corporation is a Federal Contract Bedford center is supported by 15 Symbolics Lisp machines Research Center, a designation covering the handful netted to two Vax-780 file servers, while the Washington of independent institutions that perform governmentsponsored center is supported by both a classified and an unclassified research. It is an independent, nonprofit corporation facility, with 2 Lambdas and 2 Symbolics Lisp machines designed and m.anagcd to provide long-term assistance respectively netted to Vax-780 file servers.
Evolving Systems of Knowledge
The enterprise of developing knowledge-based systems is currently witnessing great growth in popularity. The central unity of many such programs is that they interpret knowledge that is explicitly encoded as rules. While rule-based programming comes with certain clear pay-offs, further fundamental advances in research are needed to extend the scope of tasks that can be adequately represented in this fashion. This article is a statement of personal perspective by a researcher interested in fundamental issues in the symbolic representation and organization ok knowledge.