Our own early attempts (as devoted users of LISP) to use PROLOG convinced us that it would be worth the effort to create within LISP a faithful implementation of Kowalski's logic programming idea. We felt it would be very convenient to be able to set up a knowledge base of assertions inside a LISP workspace, and to compute the answers to queries simply by executing appropriate function calls.In Hayes, J. E., Michie, D., and Pao, Y.-H. (Eds.), Machine Intelligence 10. Ellis Horwood.

Discourse Processes, vol. 5, No. 1, pp. 1-32.

PROLOG is a simple and powerful progamming language based on first-order logic. This paper examines two possible extensions to the language which would generally be considered "higher-order".t The first extension introduces lambda expressions and predicate variables so that functions and relations can be treated as 'first class' data objects. We argue that this extension does not add anything to the real power of the language. The other extension concerns the introduction of set expressions to denote the set of all (provable) solutions to some goal. We argue that this extension does indeed fill a real gap in the language, but must be defined with care.In Hayes, J. E., Michie, D., and Pao, Y.-H. (Eds.), Machine Intelligence 10. Ellis Horwood.

Motor control systems are complex systems that process information. Orientation behaviour, posture control, and the manipulation of objects are examples of motor control systems which involve one or more sensory modality and various central neural processes, as well as effector systems and their immediate neuronal control mechanisms. Like all complex information processing systems, they must be analysed and understood at several different levels (see, e.g., Marr & Poggio 1977).At the lowest level there is the analysis of basic components and circuits, the neurons, their synapses, etc. At the other extreme, there is the study of the computations performed by the system — the problems it solves and the ways that it solves them — and the analysis of its logical organization in terms of its primary modules. In Hayes, J. E., Michie, D., and Pao, Y.-H. (Eds.), Machine Intelligence 10. Ellis Horwood.

Presented at the NATO Symposium Human and Artificial Intelligence, Lyon, France, October, 1981. CMU Technical Report CMU-CS-82-104. We examine computer games in order to develop concepts of the relative roles of knowledge and search. The paper concentrates on the relation between knowledge applied at leaf nodes of a search and the depth of the search that is being conducted. Each knowledge of an advantage has a projection ability (time to convert to a more permanent advantage) associated with it. The best programs appear to have the longest projection ability knowledge in them. If the application of knowledge forces a single view of a terminal situation, this may at times be very wrong. We consider the advantages of knowledge delivering a range as its output, a method for which some theory exists, but which is as yet unproven.

Reading, Mass.: Addison-Wesley

This chapter from the Mycin book is a brief overview of van Melle's Ph.D. dissertation (Stanford, Computer Science), and is a shortened and edited version of a paper appearing in Pergamon-lnfotech state of the art report on machine intelligence, pp. 249-263. Maidenhead, Berkshire, U.K.: Infotech Ltd., 1981. Mycin Book (1984)

This is an excerpt from the Handbook of Artificial Intelligence, a compendium of hundreds of articles about AI ideas, techniques, and programs being prepared at Stanford University by AI researchers and students from across the country. In addition to articles describing the specifics of various AI programming methods, the Handbook contains dozens of overview articles like this one, which attempt to give historical and scientific perspective to work in the different areas of AI research. This article is from the Handbook chapter on natural language understanding. Cross-references to other articles in the handbook have been removed-terms discussed in more detail elsewhere are italicized. Many people have contributed to this chapter, including especially Anne Gardner, James Davidson, and Terry Winograd. Avron Barr and Edward A. Feigenbaum are the Handbook's general editors.

Two premises, reflected in the title, underlie the perspective from which I will consider research in natural language processing in this article. First, progress on building computer systems that process natural languages in any meaningful sense (i.e., systems that interact reasonably with people in natural language) requires considering language as part of a larger communicative situation. Second, as the phrase “utterance and objective” suggests, regarding language as communication requires consideration of what is said literally, what is intended, and the relationship between the two.

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