Showing papers on "Knowledge representation and reasoning published in 1980"

Knowledge representation for syntactic/semantic processing

Abstract: This paper describes the RUS framework for natural language processing, in which a parser incorporating a substantial ATN grammar for English interacts with a semantic interpreter to simultaneously parse and interpret input. The structure of that interaction is discussed, including the roles played by syntactic and semantic knowledge. Several implementations of the RUS framework are currently in use, sharing the same grammar, but differing in the form of their semantic component. One of these, the PSI-KLONE system, is based on a general object-centered knowledge representation system, called KL-ONE. The operation of PSI-KLONE is described, including its use of KL-ONE to support a general inference process called "incremental description refinement." The last section of the paper discusses several important criteria for knowledge representation systems to be used in syntactic and semantic processing.

Representation of Knowledge

Abstract: : This report is the section of the Handbook of Artificial Intelligence about knowledge representation research. The Handbook is a compendium of articles about AI ideas, techniques, and systems intended for non-AI scientists, engineers, and students. The material in this report discusses the problems addressed in knowledge representation research in AI and suggests some ways of comparing the various representation schemes. Additional articles describe the AI representation techniques: logic, procedural representations, semantic nets, production systems, direct (analogical) representations, semantic primitives, and frames.

Artificial intelligence methods and systems for medical consultation

Abstract: The major AI problems that arise in designing a consultation program involve choices of knowledge representations, diagnostic interpretation strategies, and treatment planning strategies. The need to justify decisions and update the knowledge base in the light of new research findings places a premium on the modularity of a representation and the ease with which its reasoning procedures can be explained. In both diagnosis and treatment decisions, the relative advantages and disadvantages of different schemes for quantifying the uncertainty of inferences raises difficult issues of a formal logical nature, as well as many specific practical problems of system design. An important insight that has resulted from the design of several artificial intelligence systems is that robustness of performance in the presence of many uncertainty relationships can be achieved by eliciting from the expert a segmentation of knowledge that will also provide a rich network of deterministic relationships to interweave the space of hypotheses.

A representation language language

Abstract: The field of AI is strewn with knowledge representation languages. The language designer typically has one particular application domain in mind; as subsequent types of applications are tried, what had originally been useful features become undesirable limitations, and the language is overhauled or scrapped. One remedy to this bleak cycle might be to construct a representational scheme whose domain is the field of representational languages itself. Toward this end, we designed and implemented RLL, a frame-based Representation Languange Language. The components of representation languages in general (such as slots and inheritance mechanisms) and of RLL itself are encoded declaratively as frames. Modifying these frames can change the semantics of RLL, by radically altering the character of the RLL environment.

An overview of Knowledge Representation

Abstract: This is a brief overview of terminology and issues related to Knowledge Representation (here-after KR) research, intended primarily for researchers working on Semantic Data Models within Database Management and Program Specifications within Programming Languages/Software Engineering.Knowledge Representation is a central problem in Artificial Intelligence (AI) today. Its importance stems from the fact that the current design paradigm for “intelligent” systems stresses the need for expert knowledge in the system along with associated knowledge-handling facilities. This paradigm is in sharp contrast to earlier ones which might be termed “power-oriented” [Goldstein and Papert 77] in that they placed an emphasis on general purpose heuristic search techniques [Nilsson 71].

Prototypes and production rules: a knowledge representation for computer consultations

Abstract: : This thesis presents a system called CENTAUR, which demonstrates the effectiveness of representing prototypical knowledge in a combination of frames and production rules for performing computer consultations. Key knowledge representation and control structure problems in production rule systems similar to MYCIN are identified, and a set of important characteristics of the structures used for representing problem-solving knowledge is given. CENTAUR's frames, or prototypes, complement the production rules to satisfy these characteristics and represent expected patterns of data that permit a more focused, hypothesis-directed approach to problem solving. Among the characteristics identified as desirable in the representation structures are the ability to explicitly represent (a) prototypical cases, (b) the context in which knowledge is applied, and (c) the strategies for applying that knowledge. CENTAUR's prototypes consist of patterns of knowledge in the domain which serve as broad contexts, guiding the more detailed processing of the production rules. Strategies for the consultation, or control knowledge, are represented in the prototypes separately from other kinds of domain knowledge. This allows the domain expert to specify control knowledge that is specific to each prototype. Examples are presented which demonstrate how this explicit representation facilitates explanations of the system's reasoning. Further, the organization of knowledge in CENTAUR provides a useful framework for acquiring new knowledge.

On supporting the use of procedures in office work

Abstract: In this paper, we discuss the utility of AI techniques in the construction of computer-based systems that support the specification and use of procedures in office work. We begin by arguing that the real work of carrying out office procedures is different in kind from the standard computer science notions of procedure "execution". Specifically, office work often requires planning and problem solving in particular situations to determine what is to be done. This planning is based on the goals of the tasks with which the procedures are associated and takes place in the context of an inherently open-ended body of world knowledge. We explore some of the ways in which a system can provide support for such work and discuss the requirements that the nature of the work places on such support systems. We argue that the AI research fields of planning and knowledge representation provide useful paradigms and techniques for meeting those requirements, and that the requirements, in turn, present new research problems in those fields. Finally, we advocate an approach to designing such office systems that emphasizes a symbiotic relationship between system and office worker.

Failures in natural language systems: applications to data base query systems

Abstract: A significant class of failures in interactions with data base query systems are attributable to misconceptions or incomplete knowledge regarding the domain of discourse on the part of the user. This paper describes several types of user failures, namely, intensional failures of presumptions. These failures are distinguished from extensional failures of presumptions since they are dependent on the structure rather than the contents of the data base. A knowledge representation has been developed for the recognition of intensional failures that are due to the assumption of non-existent relationships between entities. Several other intensional failures which depend on more sophisticated knowledge representations are also discussed. Appropriate forms of corrective behavior are outlined which would enable the user to formulate queries directed to the solution of his/her particular task and compatible with the knowledge organization.

Research in Knowledge Representation for Natural Language Understanding

Abstract: : This report summarizes the research of BBN's ARPA-sponsored Knowledge Representation for Natural Language Understanding project during its fourth year. In it we report on advances, both in theory and implementation, in the areas of knowledge representation, natural language understanding, and abstract parallel machines. In particular, we report on theoretical advances in the knowledge representation system KL-ONE, extensions to the KL-ONE system, and new uses of KL-ONE in the domain of knowledge about graphic displays. We report on a design for a new prototype natural language understanding system, on issues in cascaded architectures for interaction among the components of a language system, and on a module for Lexical acquisition. In addition, we examine three topics in discourse: a new model of speaker meaning, which extends our previous work on speakers' intentions, an investigation of reference planning and identification, and a theory of 'one'-anaphora interpretation. Our discussion of abstract parallel machines reports on a class of algorithms that approximate Quillian's (49) ideas on the function of human memory. (Author)

Computer Science and the Representation of Knowledge

Abstract: This chapter contains sections titled: Parts and Wholes, Old and New Concepts of Knowledge and Intelligence, Research in Artificial Intelligence, Conceptual Representations, Self-Knowledge and Programming Knowledge, Editors' Postscript, References

Representation of control knowledge in expert systems

Abstract: This paper presents the results of research done on the representation of control knowledge in rule-based expert systems." It discusses the problems of representing control knowledge implicitly in object-level inference rules and presents specific examples from a MYCIN-like consultation system called PUFF. As an alternative, the explicit representation of control knowledge in slots of a frame-like data structure is demonstrated in the CENTAUR system. Explicit representation of control knowledge has significant advantages both for the acquisition and modification of domain knowledge and for explanations of how knowledge is used in the expert system.

A planner for reasoning about knowledge and action

Abstract: This paper reports recent results of research on planning systems that have the ability to deal with multiple agents and to reason about their knowledge and the actions they perform. The planner uses a knowledge representation based on the possible worlds semantics axiomatization of knowledge, belief and action advocated by Moore [5]. This work has been motivated by the need for such capabilities in natural language processing systems that will plan speech acts and natural language utterances [1, 2]. The sophisticated use of natural language requires reasoning about other agents, what they might do and what they believe, and therefore provides a suitable domain for planning to achieve goals involving belief. This paper does not directly address issues of language per se, but focuses on the problem-solving requirements of a language-using system, and describes a working system, kamp (Knowledge And Modalities Planner), that embodies the ideas reported herein.

Semantics vs. graphics - to show or not to show

Abstract: This paper describes a high-level graphical interface to databases which employs specialized knowledge about graphical symbols, the underlying database, and the database user's context in order to provide pictorial representations of data which is of concern to the user. The approach combines techniques of graphics and knowledge representation to provide more complete and more perspicuously organized answers to user queries. Techniques are presented for the representation and use of the semantic knowledge about the database contained in the data model. The knowledge of the data model allows the system to augment the response to a query with information which is relevant but not specifically requested. It also enables the data to be organized in a manner which reflects the relative importance of each of the entities and attributes within the context of the user's question. Thus the answer to the user's question is broadened in a meaningful way to provide the user with a more complete perspective of the information in the database.

The Use of Equality in Deduction and Knowledge Representation

Abstract: : This report describes a system which maintains canonical expressions for designators under a set of equalities. Substitution is used to maintain all knowledge in terms of these canonical expressions. A partial order on designators, termed the better-name relation, is used in the choice of canonical expressions. It is shown that with an appropriate better-name relation an important engineering reasoning technique, propagation of constraints, can be implemented as a special case of this substitution process. Special purpose algebraic simplification procedures are embedded such that they interact effectively with the equality system. An electrical circuit analysis system is developed which relies upon constraint propagation and algebraic simplification as primary reasoning techniques. The reasoning is guided by a better-name relation in which referentially transparent terms are preferred to referentially opaque ones. Multiple description of subcircuits are shown to interact strongly with the reasoning mechanisms.

An overview of Knowledge Representation

Abstract: This is a brief overview of terminology and issues related to Knowledge Representation (here-after KR) research, intended primarily for researchers working on Semantic Data Models within Database M...

Semiotic systems and knowledge representation

Abstract: This paper deals with cognitive processes and knowledge representation. The starting point is an analysis of an object, treated as a relational system and its representation. The formalism developed is especially convenient to capture the problems of observability and change. After these considerations, a formal theory of semiotics is outlined, allowing a new development and unified treatments (within the paradigm of fuzzy set theory) of such topics as structure of signs and their configurations (spatial and temporal), i.e. formal representations of situations and events; structure of the cognitive representations of signs, leading to the construction of a language of semantics; and structure of verbal representations of objects (their verbal copies), the latter analysed by means of the methods of mathematical linguistics, leading, among other things, to the foundations of formal text theory. As regards verbal copies, the main stress is put on cognitive constraints on descriptions imposed by the limitations of knowledge and/or observability, and constraints imposed by the language used. The properties of verbal copies can also be fruitfully related to theories of perception and memory. The set of interrelated theories presented here, and introduced for the first time by the author, allows for a compact and unified way of treating the topics which were traditionally considered separately, as various parts of psychology, philosophy or logic. As regards formal semiotics, as sketched here, it goes far beyond the notions of Peirce, leading to a system richer than taxonomical considerations, allowing for the development of semiotic theory.

A perspective for research on conceptual modelling

Abstract: This position paper is intended to provide a perspective for research on conceptual modelling carried out over the past five years at the University of Toronto and to draw some conclusions from the experiences we have accumulated. “Conceptual modelling” here refers to the activity of constructing abstract models of knowledge about some world and is synonymous with the terms “knowledge representation” and “semantic data model” as they have been used in AI and Databases respectively. Much of the research on the subject has focused on the development of descriptive tools for the description of such models. Less attention has been paid, so far, on methodologies for building such models.

Linguistic meaning and knowledge representation in automatic understanding of natural language

Abstract: The necessity of and means for distinguishing between a level of linguistic meaning and a domain of "factual knowledge" (or cognitive content) are argued for, supported by a survey of relevant operational criteria. The level of meaning is characterized as a safe base for computational applications, which allows for a set of inference rules accounting for the content (factual relations) of a given domain.

An Expert System for Automatic Codeing of Abstract Data Type Specifications

Abstract: The system ADTCOMP constructs working programs from algebraic specifications of abstract data types. It is an experimental system devised to develop methods for codifying a rather broad extent of programming knowledge necessary to generate programs from axiomatizations constituting the most abstract form of specifying data types.

Integrating a database system and programming / information environment

Abstract: Vast differences in terminology aside, there is considerable overlap between work in knowledge representation, programming language data types, and database models. Our current work on the Cedar programming environment has necessitated integrating a number of ideas in these areas.As part of the Cedar project in the Computer Science Lab at Xerox PARC, we have been constructing a database management system. The goal of the Cedar environment is to greatly increase our productivity by combining the best currently known principles from programming languages, programming tools, and user interfaces into a single integrated system. Cedar is based on the Mesa programming language [1]. The goal of our database subproject of Cedar is to provide a uniform prepackaged way to perform access to data structures, as contrasted to the current state of affairs in which Mesa programmers repeatedly re-invent the facilities we intend to provide to type, structure, index, link, robustly store, concurrently access, and cache data stored in the primary or secondary memory of one or more computers on a network.

An information presentation system for decision makers

Abstract: This paper describes a new concept for interfacing operational decision makers with their information systems. It is intended to overcome the rigidities of current architectures by enabling the decision maker to direct, modify, and manipulate the presentation of information in real-time through a highly automated interface system. The current practice of specifying a decision maker's desires to a programmer, who must in turn produce a data gathering and formatting program that interfaces with some graphics system, is unsatisfactory for the real-time needs of an ever-changing decision environment.An experimental Information Presentation System has been implemented utilizing a high-level knowledge representation language. The system manipulates general descriptions of information presentation concepts such as coordinate systems, trnasformations, display regions, display objects, and the relationships between data objects and their depictions. This paper summarizes the current state of that system and the Information Presentation System concept.

On the existence of primitive meaning units

Abstract: Knowledge representation schemes are either based on a set of primitives or not. The decision of whether or not to have a primitive-based scheme is crucial since it affects the knowledge that is stored and how that knowledge may be processed. We suggest that a knowledge representation scheme may not initially have primitives, but may evolve into a primitive-based scheme by inferring a set of primitive meaning units based on previous experience. We describe a program that infers its own primitive set and discuss how the inferred primitives may affect the organization of existing information and the subsequent incorporation of new information.

An overview of Knowledge Representation

Abstract: This is a brief overview of terminology and issues related to Knowledge Representation (here-after KR) research, intended primarily for researchers working on Semantic Data Models within Database M...

An overview of Knowledge Representation

Abstract: This is a brief overview of terminology and issues related to Knowledge Representation (here-after KR) research, intended primarily for researchers working on Semantic Data Models within Database M...

Processing of Syntax and Semantics of Natural Language by Predicate Logic of Predicate Logic

Abstract: The syntax and semantic analyses of natural language are described from the standpoint of manmachine communication. The knowledge based system KAUS(Knowledge Acquisition and Utilization System) which has capabilities of deductive inference and automatic program generation of database access is utilized for that purpose. We try to perform syntax and semantic analyses of English sentences more or less conccurently by defining the correspondence between the basic patterns of English and the extended atomic formula in the framework of KAUS. Knowledge representation based on sets and logic, the sentence analysis utilizing this knowledge are given with some examples.

Application of Symbolic Processing to Command and Control: An Advanced Information Presentation System

Abstract: : Last year the Advanced Information Presentation System (AIPS) had reached the point of a first-pass implementation. Some analysis and experimentation with that system and its internal representation structure revealed areas where the knowledge structure was inadequate -- either not epistemologically sound or not computationally reasonable. During this year we have conceptualized a new structure for the system and have begun the task of implementing our next generation AIPS system. An effort has been made to modularize the system's knowledge structure. This has led to a totally new declarative architecture for the system. This architecture promises to provide a system whose capabilities are more easily extended into the realm of 'intelligent' behavior. This project has been active in helping to evolve the KL-ONE knowledge representation language. Some of the tools which have been developed this year for implementing in KL-ONE, especially the CKLONE network building operators are described.

Application of Symbolic Processing to Command and Control

Abstract: : This paper describes an effort to evolve and apply a symbolic processing paradigm for Command and Control (C2) systems. The specific application discussed is an 'intelligent' graphics interface to support time- critical C2 tasks. This Advanced Interactive Presentation System (AIPS) replaces the separate and specialized graphics interfaces of individual decision-support application programs, providing the user with a highly automated agent through which to interactively direct and modify the generation of displays whose content cuts across sub-system boundaries. The key to providing this high level of automation lies in the correct representation of knowledge about graphics, the display device, the application domain, and the user's needs. An experimental AIPS has been constructed utilizing a high-level knowledge representation language (KLONE) implemented as part of this effort.