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Models of learning systems

Classics

"The terms adaptation, learning, concept-formation, induction, self-organization, and self-repair have all been used in the context of learning system (LS) research. The research has been conducted within many different scientific communities, however, and these terms have come to have a variety of meanings. It is therefore often difficult to recognize that problems which are described differently may in fact be identical. Learning system models as well are often tuned to the require- ments of a particular discipline and are not suitable for application in related disciplines."In Encyclopedia of Computer Science and Technology, Vol. 11. Dekker


Pattern-based representation of chess end-game knowledge

Classics

Master skill--operational in the sense-t'hat it can be run on Another form of the'Master skill' aspiration aims at correct'strong mastery' in this sense is attainable for the complete None of the above listed endgames contains anything problematical from a Master's point of view and computer programs Using a vocabulary which is defined in Kmoch's (1959) 'An enemy pawn ahead on the same file is a counterpawn, Some of these relations may be very useful if developed further. For expmple, if a pawn is'overloaded', in that it is pefforming Defence Diagram, see Figure 1). A rule is applied'to a position (in a manner familiar to'forcing tree' that guarantees the achievement of better-goals The'and-or' tree search, carried out by module 1 of the AU Figure 1 The ADD corresponding to the position shown in Figure 1. The Computer Journal ' HOW DIFFICULT IS THE KNKR PROBLEM? Longest variation in Fine before capture of the Knight: 24 moves; longest known variation 27 moves.


Informality in program specification

Classics

This paper is concerned primarily with (1) the procedure by which process-oriented specifications are obtained from goal-oriented requirement specifications and (2) computer-based tools for their construction. It first determines some attributes of a suitable process-oriented specification language, then examines the reasons why specifications would still be difficult to write in such a language. The key to overcoming these difficulties seems to be the careful introduction of informality based on partial, rather than complete, descriptions and the use of a computer-based tool that uses context extensively to complete these descriptions during the process of constructing a well-formed specification. Some results obtained by a running prototype of such a computer-based tool on a few informal example specifications are presented and, finally, some of the techniques used by this phototype system are discussed.


The representation and use of focus in a system for understanding dialogs

Classics

THE REPRESENTATION AND USE OF FOCUS IN A SYSTEM FOR UNDERSTANDING DIALOGS Barbara J. Grosz Artificial Intelligence Center SRI International, Menlo Park, California 94025 ABSTRACT As a dialog progresses the objects and actions that are most relevant to the conversation, and hence in the focus of attention of the dialog participants, change. This paper describes a representation of focus for language understanding systems, emphasizing its use in understanding taskoriented dialogs. The representation highlights that part of the knowledge base relevant at a given point in a dialog. A model of the task is used both to structure the focus representation and to provide an index into potentially relevant concepts in the knowledge base The use of the focus representation to make retrieval of items from the knowledge base more efficient is described. I INTRODUCTION To understand the sentences in a discourse, a computer system, like a person, must have knowledge about the domain of the discourse. However, the knowledge required to understand even simple, reallife domains is so extensive that it will overwhelm a system that does not apply it selectively. This means that the ability to focus on the subset of knowledge relevant to a particular situation is crucial. This paper addresses the problem of focus from the perspective of building a computer system that can participate in a task-oriented dialog. A representation for focus is presented; its use is illustrated by showing how the referents of definite noun phrases are identified. A combination of contextual factors influences the interpretation of an utterance. In fact, what is usually meant by "the context of an utterance" is precisely that set of constraints which together direct attention to the concepts of interest in the discourse in which the utterance occurs. Both the preceding discourse context - - the utterances that have already occurred -- and the situational context -- the environment in which an utterance occurs -- affect the interpretation of the utterance. For a dialog, the situational context includes the physical environment, the social setting, and the relationship between the participants in the dialog. This paper shows how the task and dialog contexts combine to provide a focus on those concepts relevant to the interpretation of utterances in task-oriented dialogs.


Model representations and control structures in image understanding

Classics

Hierarchies are observed in the levels of description used in image understanding along a few dimensions: processing unit, detail, composition and scene/view distinction. Emphasis is placed on the importance of explicitly handling the hierarchies both in representing knowledge and in using it. A scheme of "knowledge block" representation which is structured along the processing-unit hierarchy is also presented. I. INTRODUCTION Image Understanding System(IUS) constructs a description of the scene being viewed from an array of image sensory data: intensity, color, and sometimes range data. Image understanding is best characterized by description, whereas pattern recognition by classification, and image processing by image output.


Knowledge structures and language boundaries

Classics

I shall refer to such restrictions as preference restrictions, because of the way the present NLUS is already able to accept natural language that violates preferences, as (1) does (see recap in next section for more detail). Such usage as (s) will be referred to as extended, or preference violating, and these will serve instead of the more literary and philosophical term "metaphorical". It is an important assumption of this paper that such usage is the norm in ordinary everyday language use, and cannot be relegated to the realm of the exceptional, or the odd, and so dealt with by considerations of "performance". On the contrary it is, I would argue, central to our language capabilities, and any theory of language must have something concrete to say about it. Even if the newspaper usages above are "extended", I would suggest that anyone who could not grasp these extension could not be said to understand English properly (given adequate knowledge from which to extend, and we shall come to that.) It will be obvious already that the commitment to a norm implies a corresponding commitment to general everyday language as a proper topic for Al.



Levels of complexity in discourse for anaphora disambiguation and speech act interpretation

Classics

U.S.A. Abstract: This paper presents a discussion of means of describing the discourse and its components which makes speech act interpretation and anaphora disambiguation possible with minimal search of the knowledge in the database. A portion of this paper will consider how a frames representation of sentences and common sense knowledge provides a mechanism for representing the postulated discourse components. Finally some discussion of the use of the discourse model and of frames in a discourse understanding program for a personal assistant will be presented. Introduction The person who communicates with a personal assistant, whether human or machine, wants to request some action of the assistant via sentences in English. Generally, a single sentence is insufficient to capture all the information that is to be given as well as an unnatural way to make a request. However, as several example dialogues below will show, the human user does not tightly relate the sentences s/he speaks about a particular subject. It is instead the job of the hearer to interpret how the incoming sentence is related to the previous discourse. Each sentence or clause of a discourse that makes some demand upon the hearer must be interpreted for the kind of demand being made. These demands are generally referred to as speech acts {1}. However, the speech acts are not just strings of individual requests. They have a connecting pattern which the hearer must extract as the discourse goes on. Thus the hearer's task is twofold: to interpret the speech act in a clause and to relate that speech act to the overall discourse. In this paper this two-pronged task will be referred to as speech act interpretation. Closely associated with speech act interpretation is the process of understanding what the various noun and pronoun phrases of the incoming sentence refer to. Speakers denote previously mentioned objects in a variety of ways with apparent ambiguity in the choice of referents.


In defence of logic

Classics

This view is nominalism, and leads to a quite different sort of semantic intuition, in which, for example, red denotes not a property of physical individuals, but the (rather disconnected) individual consisting of all pieces of red stuff in the world. Other similar confusions are also made. For example, logic is no worse (and no better) than Conceptual Dependency at representing warm, human facts about people hitting each other, (4) Logic doesn't give "the ultimate in decomposition of knowledge". Winograd, in his widely cited discussion [23] of the assertional/procedural controversy, draws a distinction between logic's atomistic view of knowledge, in which a representation is seen as a set of separate disconnected facts, and the proceduralist's holistic view in which interactions between procedures have prominence. But this is exactly the opposite of the truth.