E1AR0002@SMUVM1.BITNET (11/11/86)
TECHNICAL NOTE: 246\hfill PRICE: \$16.00\\[0.01in] \noindent TITLE: DEDUCTIVE SYNTHESIS OF THE UNIFICATION ALGORITHM\\ AUTHORS: ZOHAR MANNA and RICHARD WALDINGER\\ DATE: JULY 1981\\[0.01in] ABSTRACT: The deductive approach is a formal program construction method in which the derivation of a program from a given specification is regarded as a theorem-proving task. To construct a program whose output satisfies the conditions of the specification, we prove a theorem stating the existence of such an output. The proof is restricted to be sufficiently constructive so that a program computing the desired output can be extracted directly from the proof. The program we obtain is applicative and may consist of several mutually recursive procedures. The proof constitutes a demonstration of the correctness of this program. To exhibit the full power of the deductive approach, we apply it to a nontrivial example--the synthesis of a unification algorithm. Unification is the process of finding a common instance of two expressions. Algorithms to perform unification have been central to many theorem-proving systems and to some programming-language processors. The task of deriving a unification algorithm automatically is beyond the power of existing program synthesis systems. In this paper we use the deductive approach to derive an algorithm from a simple, high-level specification of the unification task. We will identify some of the capabilities required of a theorem-proving system to perform this derivation automatically.\\ -------------------------------------------------------------------------------- -------------------------------------------------\\ TECHNICAL NOTE: 248\hfill PRICE: \$10.00\\[0.01in] \noindent TITLE: ARTIFICIAL INTELLIGENCE: ENGINEERING, SCIENCE OR SLOGAN?\\ AUTHOR: NILS J. NILSSON\\ DATE: JULY 1981\\[0.01in] ABSTRACT: This paper presents the view that artificial intelligence (AI) is primarily concerned with propositional languages for representing knowledge and with techniques for manipulating these representations. In this respect, AI is analogous to applied mathematics; its representations and techniques can be applied in a variety of other subject areas. Typically, AI research is (or should be) more concerned with the general form and properties of representational languages and methods than it is with the content being described by these languages. Notable exceptions involve commonsense'' knowledge about the everyday world (no other specialty claims this subject area as its own), and world (no knowledge about the properties and uses of knowledge itself). In these areas AI is concerned with content as well as form. We also observe that the technology that seems to underlie peripheral sensory and motor activities (analogous to low-level animal or human vision and muscle control) seems to be quite different from the technology that seems to underlie cognitive reasoning and problem solving. Some definitions of AI would include peripheral as well as cognitive processes; here we argue against including the peripheral processes.\\ -------------------------------------------------------------------------------- -------------------------------------------------\\ TECHNICAL NOTE: 251\hfill PRICE: \$14.00\\[0.01in] \noindent TITLE: PRACTICAL NATURAL LANGUAGE PROCESSING BY COMPUTER\\ AUTHOR: ROBERT C. MOORE\\ DATE: OCTOBER 1981\\[0.01in] ABSTRACT: This paper describes the state of the art in practical computer systems for natural-language processing. We first consider why one would want to use natural language to communicate with computers at all, looking at both general issues and specific applications. Next we examine what it really means for a system to have a natural-language capability. This is followed by a discussion of some major limitations of current technology. The bulk of the paper is devoted to looking in detail at a single application of natural-language processing: database retrieval by natural-language query. We lay out an overall system architecture, explaining what types of processing and information are required. Then we look at two general classes of systems, special-purpose and general-purpose, explaining how they differ and their relative advantages and disadvantages. Afterwards we point out some remaining problems that will require addition basic research. Finally we conclude by discussing when language-processing technology at various levels of capability is likely to be commercially practical, and what is may cost to develop and use applications of that technology.\\ -------------------------------------------------------------------------------- -------------------------------------------------\\ TECHNICAL NOTE: 252\hfill PRICE: \$12.00\\[0.01in] \noindent TITLE: MACHINE LEARNING FOR INFORMATION MANAGEMENT\\ AUTHORS: NORMAN HAAS and GARY HENDRIX\\ DATE: JULY 1981\\[0.01in] ABSTRACT: This paper discusses machine learning in the context of information management. The core idea is that of a compiler system that can hold a conversation with a user in English about his specific domain of interest, subsequently retrieve and display information conveyed by the user, and apply various types of external software systems to solve user problems. The specific learning problems discussed is how to enable computer systems to acquire information about domains with which they are unfamiliar from people who are expert in those domains, but have little or no training in computer science. The information to be acquired is that needed to support question-answering or fact retrieval tasks, and the type of learning to be employed is learning by being told. Reflecting the intimate connection between language and reasoning, this paper is largely concerned with the problems of learning concepts and language simultaneously.\\ -------------------------------------------------------------------------------- -------------------------------------------------\\ TECHNICAL NOTE: 253\hfill PRICE: \$20.00\\[-0.15in] \begin{tabbing} \noindent TITLE: \= COMPUTATIONAL STRATEGIES FOR ANALYZING THE ORGANIZATION\\ \> AND USE OF INFORMATION\\ AUTHOR: DONALD E. WALKER\\ DATE: JULY 1981\\[-0.15in] \end{tabbing} ABSTRACT: This chapter describes new developments in computer-based procedures that can improve our understanding of how people organize and use information. Relevant recent research in information science, computational linguistics, and artificial intelligence is reviewed. A program of research is presented that is producing systems that make it possible to study the organization and use of information and, at the same time, provide more effective support for people engaged in those activities.\\ -------------------------------------------------------------------------------- -------------------------------------------------\\ TECHNICAL NOTE: 254\hfill PRICE: \$20.00\\[0.01in] \noindent TITLE: A TEAM USER'S GUIDE\\ AUTHORS: ARMAR A. ARCHBOLD, BARBARA GROSZ, and DANIEL SAGALOWICZ\\ DATE: DECEMBER 1981\\[0.01in] ABSTRACT: TEAM (Transportable English Data Access Manager) is a computer system designed to acquire information about a (local or remote) database, and subsequently to interpret and answer questions addressed to the database in a subset of natural language. The system currently includes an interactive program that acquires information about a database from the database administrator. The user is asked how the database is to be structured and what language is to be used to talk about its contents. The program augments the following components of a core natural language access system: * The lexicon * The conceptual model of the domain (or conceptual schema) * The structural model of the database (or database schema). After these steps have been completed, the system accepts natural-language questions about the database contents and, to the EXTENT it is able, provides relevant responses.\\ -------------------------------------------------------------------------------- -------------------------------------------------\\ TECHNICAL NOTE: 255\hfill PRICE: \$14.00\\[0.01in] \noindent TITLE: THE DATABASE AS MODEL: A METATHEORETIC APPROACH\\ AUTHOR: KURT KONOLIGE\\ DATE: SEPTEMBER 1981\\[0.01in] ABSTRACT: This paper presents a method of formally representing the information that is available to a user of a relational database. The intended application area is deductive question-answering systems that must access an existing relational database. To respond intelligently to user inquiries, such systems must have a more complete representation of the domain of discourse than is generally available in the tuple sets of a relational database. Given this more expressive representation, the problem then arises of how to reconcile the information present in the database with the domain representation, so that database queries can be derived to answer the user's inquiries. Here we take the formal approach of describing a relational database as the model of a first-order language. Another first-order language, the metalanguage, is used both to represent the domain of discourse, and to describe the relationship of the database to the domain. The formal advantages of this approach are presented and contrasted with other work in the area.\\ -------------------------------------------------------------------------------- -------------------------------------------------\\ TECHNICAL NOTE: 256\hfill PRICE: \$14.00\\[0.01in] \noindent TITLE: A PROBABILISTIC MODEL FOR UNCERTAIN PROBLEM SOLVING\\ AUTHOR: ARTHUR M. FARLEY\\ DATE: DECEMBER 1981\\[0.01in] ABSTRACT: With growing interest in the application of research to problems that arise in real-world contexts, issues raised by consideration of uncertain states and unreliable operators are receiving increased attention in artificial intelligence research. In this paper, a model is presented for dealing with such concerns. The model is a probabilistic generalization of the familiar notion of problem space. The specification of uncertain states and unreliable operators is discussed. Problem-solving search methods are described. The need for information gathering is established. Search methods are generalized to produce tree-structured plans incorporating the use of such operators. Several application domains for our model are discussed.\\ -------------------------------------------------------------------------------- -------------------------------------------------\\ TECHNICAL NOTE: 257\hfill PRICE: \$20.00\\[0.01in] \noindent TITLE: RESEARCH ON NATURAL-LANGUAGE PROCESSING AT SRI\\ AUTHOR: BARBARA J. GROSZ\\ DATE: NOVEMBER 1981\\[0.01in] ABSTRACT: Research on natural-language processing at SRI spans a broad spectrum of activity. Two of our major current efforts are a pair of research projects under the sponsorship of the Defense Advanced Research Projects Agency. The TEAM project is intended to provide natural-language access to large databases via systems that are easily adaptable to a wide range of new application domains. The KLAUS project is a longer-range effort to address basic research problems in natural-language semantics, commonsense reasoning, and the pragmatics of natural-language communication. These two projects share a common core-language-processing system called DIALOGIC.\\ -------------------------------------------------------------------------------- -------------------------------------------------\\ TECHNICAL NOTE: 258\hfill PRICE: \$10.00\\[-0.15in] \begin{tabbing} \noindent TITLE: \= PARALLELISM IN PLANNING AND PROBLEM SOLVING:\\ \> REASONING ABOUT RESOURCES\\ AUTHOR: DAVID E. WILKINS\\ DATE: JANUARY 1982\\[-0.15in] \end{tabbing} ABSTRACT: The implications of allowing parallel actions in a plan or problem solution are discussed. The planning system should take advantage of helpful interactions between parallel branches, must detect harmful interactions, and, if possible, remedy them. This paper describes what is involved in this and presents some new techniques that are implemented in an actual planning system and are useful in seeking solutions to these problems. The most important of these techniques, reasoning about resources, is emphasized and explained.\\ -------------------------------------------------------------------------------- -------------------------------------------------\\ TECHNICAL NOTE: 259\hfill PRICE: \$20.00\\[0.01in] \noindent TITLE: PLANNING NATURAL-LANGUAGE UTTERANCES TO SATISFY MULTIPLE GOALS\\ AUTHOR: DOUGLAS E. APPELT\\ DATE: MARCH 1982\\[0.01in] ABSTRACT: This dissertation presents the results of research on a planning formalism for a theory of natural-language generation that will support the generation of utterances that satisfy multiple goals. Previous research in the area of computer generation of natural-language utterances has concentrated two aspects of language production: (1) the process of producing surface syntactic forms from an underlying representation, and (2) the planning of illocutionary acts to satisfy the speaker's goals. This work concentrates on the interaction between these two aspects of language generation and considers the overall problem to be one of refining the specification of an illocutionary act into a surface syntactic form, emphasizing the problems of achieving multiple goals in a single utterance. Planning utterances requires an ability to reason in detail about what the hearer knows and wants. A formalism, based on a possible-worlds semantics of an intentional logic of knowledge and action, was used for representing the effects of illocutionary acts and the speaker's beliefs about the hearer's knowledge of the world. Techniques are described that enable a planning system to use the representation effectively. The language-planning theory and knowledge representation are embodied in a computer system called KAMP (Knowledge And Modalities Planner), which plans both physical and linguistic actions, given a high-level description of the speaker's goals. The research has application to the design of gracefully interacting computer systems, multiple-agent planning systems, and the planning of knowledge acquisition.\\ -------------------------------------------------------------------------------- -------------------------------------------------\\ TECHNICAL NOTE: 260\hfill PRICE: \$18.00\\[0.01in] \noindent TITLE: SPECIAL RELATIONS IN PROGRAM-SYNTHETIC DEDUCTION\\ AUTHORS: ZOHAR MANNA and RICHARD WALDINGER\\ DATE: MARCH 1982\\[0.01in] ABSTRACT: Program synthesis is the automated deviation of a computer program from a given specification. In the \underline{deductive} \underline{approach}, the synthesis of a program is regarded as a theorem-proving problem; the desired program is constructed as a by-product of the proof. This paper presents a formal deduction system for program synthesis, with special features for handling equality, the equivalence connective, and ordering relations. In proving theorems involving the equivalence connective, it is awkward to remove all the quantifiers before attempting the proof. The system therefore deals with \underline{partially} \underline{skolemized} \underline{sentences}, in which some of the quantifiers may be left in place. A rule is provided for removing individual quantifiers when required after the proof is under way. The system is also \underline{nonclausal}; i.e., the theorem does not need to be put into conjunctive normal form. The equivalence, implication, and other connectives may be left intact.\\ -------------------------------------------------------------------------------- -------------------------------------------------\\ TECHNICAL NOTE: 261\hfill PRICE: \$14.00\\[0.01in] \noindent TITLE: COMPUTATIONAL STEREO\\ AUTHORS: STEPHEN T. BARNARD and MARTIN A. FISCHLER\\ DATE: MARCH 1982\\[0.01in] ABSTRACT: Perception of depth is a central problem in machine vision. Stereo is an attractive technique for depth perception because, compared to monocular techniques, it leads to more direct, unambiguous, and quantitative depth measurements, and unlike such active" approaches as radar and laser ranging, it is suitable in almost all application domains. We broadly define computational stereo as the recovery of the three-dimensional characteristics of a scene from multiple images taken from different points of view. The first part of the paper identifies and discusses each of the functional components of the computational stereo paradigm: image acquisition, camera modeling, feature acquisition, matching, depth determination, and interpolation. The second part discusses the criteria that are important for evaluating the effectiveness of various computational stereo techniques. The third part surveys a representative sampling of computational stereo research.\\ -------------------------------------------------------------------------------- -------------------------------------------------\\ TECHNICAL NOTE: 263R\hfill PRICE: \$10.00\\[0.01in] \noindent TITLE: TEAM: A TRANSPORTABLE NATURAL-LANGUAGE INTERFACE SYSTEM\\ AUTHOR: BARBARA J. GROSZ\\ DATE: NOVEMBER 1982\\[0.01in] ABSTRACT: A major benefit of using natural language to access the information in a database is that it shifts onto the system to burden of mediating between two views of the data: the way in which the data is stored (the database view''), and the way in which an end-user thinks about it (the user's view''). Database information is recorded in terms of files, records, and fields, while natural-language expressions refer to the same information in terms of entities and relationships in the world. A major problem in constructing a natural-language interface is determining how to encode and use the information needed to bridge these two views. Current natural-language interface systems require extensive efforts by specialists in natural-language processing to provide them with the information they need to do the bridging. The systems are, in effect, handtailored to provide access to particular databases. This paper focuses on the problem of constructing \underline{transportable} natural-language interfaces, i.e., systems that can be adapted to provide access to databases for which they were not specifically handtailored. It describes an initial version of a transportable system, called TEAM (for \underline{T}ransportable \underline{E}nglish \underline{A}ccess Data \underline{M}anager). The hypothesis underlying the research described in this paper is that the information required for the adaptation can be obtained through an interactive dialogue with database management personnel who are not familiar with natural-language processing techniques.\\ -------------------------------------------------------------------------------- -------------------------------------------------\\ -------