Although in both economics and cognitive science the meaning-bearing in generative grammar), decision theory, and even objects (or the instantiation of the symbols) are physical, parts of anthropology (eg, Levi-Strauss). The functionalist it is only by referring to their symbolic or referential Perspective 2 is now quite general in psychology and philosophy character that we can explain the observed regularities in of mind as well as in engineering, where it is the resulting behavior.

The five-year ARPA-funded speech project that began at that time made understanding, rather than The transduction from speech to meaning must be mediated recognition, the primary research goal. It was felt that a by a variety of components that utilize diverse system's ability to respond intelligently to speech was a knowledge sources (KSs) because the speech signal encodes, more meaningful criterion for the evaluation of speech in a highly compressed and integrated fashion, systems. In addition, it was believed that the speech signal many different types of information relevant to the recovery was an impoverished source of information, and of meaning. This knowledge-based approach contrasts knowledge of the context of an utterance was essential for with that taken in whole-word template-matching systems; its successful recognition and interpretation. Speech-recognition variability in the pronunciation of words in connected systems based on dynamic programming, pattern-matching speech is no longer seen as a hindrance to pattern techniques have been developed for utterances matching but rather as an important source of information, that consist solely of isolated words chosen from a eg, concerning the location of word boundaries small vocabulary, and to a lesser extent, the same techniques (Church, 1983) or of contextually important (stressed) information have been extended to connected sequences of in the utterance. Figure 1 illustrates one possi-words Rabiner and Levinson (1981).

By studying biological systems, Several definitions for the term robot have been proposed principles may be discovered that can be used, perhaps by (Jablonowski and Posey, 1985). None of these definitions analogy, to improve the functional components of a robot are adequate because they exclude robot intelligence of as well as their cooperation.

Step 6 is a goal-assertion the input, another algorithm might result. Thus one could resolution that functions similarly to the goal-goal resolution break a into a[1],..., a [length(a)/2] and a [length(a)/ above. The final synthesized program is: 2 1],..., a[length(a)] and find an algorithm that recursively calls f on both the first and second halves of its f(x) if x NIL then 0 else car(x) f(cdr(x)).

The introduction to this paper discusses the notion of human creativity, and raises the question of designing a "creative" computer program. Creativity is assumed not to imply the possession of special mental equipment: a theory of creativity should be a theory of intellect which accounts for normal performance and enhanced performance in the same terms. Art-making is described as a form of creative behavior which demonstrates the importance of non-rational features. It is argued that the central feature of "enhanced" intellectual performance is the individual's ability to modify, by the manipulation of internal representations, his/her own mental structures. The processes of representation constrain the actions of the representer, and thus what he/she is capable of representing. Part Two examines the anatomy of Representations in technological terms: the means, the skills, and the theory of operation (of the representation process) which the individual may bring to bear, and the constraints which result. It is proposed that representations represent lower-order representations (internal models), not the external world, and that the making of external objects plays a role in "checking" internal representations of explicit information, is shown as a culturallymodulated phenomenon distinct from evocation, which draws upon more inherently human capacities. Part Three describes a program designed to investigate the interaction of a primitive internal model of world objects with a "representational technology"--the technology by means of which the -ivinternal

See Caus-al consistency Certainty factor, 66, 86, 106, 122, 233, 245. of knowledge bases, 96, 128,253,467,470 See also Uncertainty

Paper presented at the IPN Symposium 7: Formalized Theories of Thinking and Learning and Their Implications for Science Instruction.

How do practicing physicians make clinical decisions? What techniques can we use in the computer to produce programs that exhibit medical expertise? Our interest in these questions is motivated by our desire: 1. to provide (by computer) expert medical consultation to general practitioners or paramedical personnel in communities where such consultation is normally unavailable; 2. to come to understand the reasoning processes of expert doctors so that we may improve the teaching of their skills to medical students; and 3. to advance the techniques of artificial intelligence, especially as applied to medicine (AIM), to support our other goals. In other publications, we have described research by our group on programs to take the history of the present illness of a patient with renal disease (Pauker and Gorry, 1976; Szolovits and Pauker, 1976) and to advise the physician in the administration of the drug digitalis to patients with heart disease (Gorry et al., 1978; Silverman, 1975; Swartout, 1977).

JANICE S. AIKINS Dr. Aikins received her Ph.D. in computer science from Stanford University in 1980. She is currently a research computer scientist at IBM's Palo Alto Scientific Center. She specializes in designing systems with an emphasis on the explicit representation of control knowledge in expert systems. ROBERT L. BLUM Dr. Blum received his M.D. from the University of California Medical School at San Francisco in 1973. From 1973 to 1976 he did an internship and residency in the Department of Internal Medicine at the Kaiser Foundation Hospital in Oakland, California, where he was chief resident in 1976.

In the present paper, a general approach to structuring medical knowledge for computer-aided diagnosis and therapy is presented. We have developed a representation that models disease processes as a causal-associational network (CASNET). This model-based method has been used successfully in designing a consultation program for the diagnosis and long-term treatment of the glaucomas. The consultation program uses a set of general decision-making strategies in conjunction with a class of causal-associational models (Kulikowski and Weiss, 1971; Weiss, 1974). In this paper, examples will be given from a CASNET model of glaucoma.