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  • 1
    Electronic Resource
    Electronic Resource
    Palo Alto, Calif. : Annual Reviews
    Annual Review of Computer Science 3 (1988), S. 1-22 
    ISSN: 8756-7016
    Source: Annual Reviews Electronic Back Volume Collection 1932-2001ff
    Topics: Computer Science
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  • 2
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    Palo Alto, Calif. : Annual Reviews
    Annual Review of Computer Science 3 (1988), S. 23-58 
    ISSN: 8756-7016
    Source: Annual Reviews Electronic Back Volume Collection 1932-2001ff
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    Palo Alto, Calif. : Annual Reviews
    Annual Review of Computer Science 3 (1988), S. 59-84 
    ISSN: 8756-7016
    Source: Annual Reviews Electronic Back Volume Collection 1932-2001ff
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    Palo Alto, Calif. : Annual Reviews
    Annual Review of Computer Science 3 (1988), S. 85-119 
    ISSN: 8756-7016
    Source: Annual Reviews Electronic Back Volume Collection 1932-2001ff
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    Palo Alto, Calif. : Annual Reviews
    Annual Review of Computer Science 3 (1988), S. 121-146 
    ISSN: 8756-7016
    Source: Annual Reviews Electronic Back Volume Collection 1932-2001ff
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    Palo Alto, Calif. : Annual Reviews
    Annual Review of Computer Science 3 (1988), S. 147-165 
    ISSN: 8756-7016
    Source: Annual Reviews Electronic Back Volume Collection 1932-2001ff
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    Palo Alto, Calif. : Annual Reviews
    Annual Review of Computer Science 3 (1988), S. 167-195 
    ISSN: 8756-7016
    Source: Annual Reviews Electronic Back Volume Collection 1932-2001ff
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    Palo Alto, Calif. : Annual Reviews
    Annual Review of Computer Science 3 (1988), S. 197-232 
    ISSN: 8756-7016
    Source: Annual Reviews Electronic Back Volume Collection 1932-2001ff
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    Palo Alto, Calif. : Annual Reviews
    Annual Review of Computer Science 3 (1988), S. 233-283 
    ISSN: 8756-7016
    Source: Annual Reviews Electronic Back Volume Collection 1932-2001ff
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    Palo Alto, Calif. : Annual Reviews
    Annual Review of Computer Science 3 (1988), S. 317-348 
    ISSN: 8756-7016
    Source: Annual Reviews Electronic Back Volume Collection 1932-2001ff
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    Palo Alto, Calif. : Annual Reviews
    Annual Review of Computer Science 3 (1988), S. 349-387 
    ISSN: 8756-7016
    Source: Annual Reviews Electronic Back Volume Collection 1932-2001ff
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    Palo Alto, Calif. : Annual Reviews
    Annual Review of Computer Science 3 (1988), S. 285-316 
    ISSN: 8756-7016
    Source: Annual Reviews Electronic Back Volume Collection 1932-2001ff
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    Palo Alto, Calif. : Annual Reviews
    Annual Review of Computer Science 3 (1988), S. 389-411 
    ISSN: 8756-7016
    Source: Annual Reviews Electronic Back Volume Collection 1932-2001ff
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  • 14
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    Oxford, UK : Blackwell Publishing Ltd
    Computational intelligence 4 (1988), S. 0 
    ISSN: 1467-8640
    Source: Blackwell Publishing Journal Backfiles 1879-2005
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    Oxford, UK : Blackwell Publishing Ltd
    Computational intelligence 4 (1988), S. 0 
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    Computational intelligence 4 (1988), S. 0 
    ISSN: 1467-8640
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Notes: We realize a computer simulation of children's reasoning in arithmetic word problem solving. The model parses the terms provided to the system in natural language and, while it performs this task, it tries to build its representation of the described situation by the way that the child elaborates a mental problem representation. This image results from three components: semantic knowledge, text comprehension process, and problem-solving strategies.We emphasize the adequacy, on one hand, between the knowledge representation and manipulation by an object formalism and, on the other hand, between the structure and the use of knowledge interacting in this application.The specific aspect of our model is that the internal representation is realized in an object-oriented language whose main properties are accurately exploited. This choice allows one to combine the descriptive characteristics of each piece of knowledge with its implication in the progress of the process.The program is supported by the analysis of individual protocols of some children: they allow us to hypothesize on the way the children modify their problem representation during the solving task.We describe the main objects of the model. Then we simulate on the terms of a problem, the way that the process is driven by expectations of contextually relevant information.
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    Oxford, UK : Blackwell Publishing Ltd
    Computational intelligence 4 (1988), S. 0 
    ISSN: 1467-8640
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Notes: It is currently thought in the knowledge-based systems (KBS) domain that sophisticated tools are necessary for helping an expert with the difficult task of knowledge acquisition. The problem of detecting inconsistencies is especially crucial. The risk of inconsistencies increases with the size of the knowledge base; for large knowledge bases, detecting inconsistencies “by hand” or even by a superficial survey of the knowledge base is impossible. Indeed, most inconsistencies are due to the interaction between several rules via often deep deductions. In this paper, we first state the problem and define our approach in the framework of classical logic. We then describe a complete method to prove the consistency (or the inconsistency) of knowledge bases that we have implemented in the COVADIS system.
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    Computational intelligence 4 (1988), S. 0 
    ISSN: 1467-8640
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Notes: This paper provides a systematic treatment of possibly imprecisely or vaguely specified numerical quantifiers in default syllogisms, following an approach initiated by Zadeh. The obtained propagation rules are derived from simple properties of relative cardinality or, equivalently, conditional probability. Uncertainty in the description of numerical quantifiers is handled using possibility theory and, particularly, fuzzy arithmetic. The advantages of this default reasoning method are its ability to model any kind of quantifier and to build new defaults by chaining existing ones, in a rigorous manner. This approach also emphasizes the difference between two types of uncertain pieces of knowledge, i.e., conjectures versus general rules.
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    Computational intelligence 4 (1988), S. 0 
    ISSN: 1467-8640
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Notes: GETA (Groupe d'études pour la traduction automatique) is a research team working basically in the domain of machine translation. GETA's software system, ARIANE-78, has been tested over various pairs of relatively unrelated languages. Being a product of the late seventies, the system misses out on some of the artificial intelligence technology, particularly that of the eighties. Nevertheless, GETA carries out some research related to artificial intelligence within a general effort to bring improvements to the current system. This paper reports on an effort to embed such work within the framework of an entirely new system based on ideas from expert systems, significantly departing from the methodology of the current system (and that of other currently implemented machine translation systems). The proposed architecture aims for total modularity and flexibility and some degree of intelligence.
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    Oxford, UK : Blackwell Publishing Ltd
    Computational intelligence 4 (1988), S. 0 
    ISSN: 1467-8640
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Notes: This paper describes a dialogue-based system which is intended as an intelligent natural language interface to the French Yellow Pages. We do not assume that the user knows how the Yellow Pages are organized, and we paraphrase his request, if necessary, so as to better search for the desired information. We do, however, assume that the reason the user is on line is to find an address and phone number for some supplier.There are three basic modules used in our system: parser, dialogue manager, and generator. The first two exist (and are constantly being extended); the generation module is still only a set of functional specifications which will be outlined later in this article.
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    Oxford, UK : Blackwell Publishing Ltd
    Computational intelligence 4 (1988), S. 0 
    ISSN: 1467-8640
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Notes: Logical omniscience may be described (roughly) as the state of affairs in which an agent explicitly believes anything which is logically entailed by that agent's beliefs. It is widely agreed that humans are not logically omniscient, and that an adequate formal model of belief, coupled with a correct semantic theory, would not entail logical omniscience. Recently, two prominent models of belief have emerged which purport both to avoid logical omniscience and to provide an intuitively appealing semantics. The first of these models is due to Levesque (1984b); the second to Fagin and Halpem (1985). It is argued herein that each of these models faces serious difficulties. Detailed criticisms are presented for each model, and a computationally oriented theory of intensions is presented which provides the foundation for a new formal model of belief. This formal model is presented in a decidable subset of first-order logic and is shown to provide a solution to the general problem of logical omniscience. The model provides for the possibility of belief revision and places no a priori restrictions upon an agent's representation language.
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    Computational intelligence 4 (1988), S. 0 
    ISSN: 1467-8640
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Notes: The relative expressive power of a sentential operator □α is compared to that of a syntactical predicate L(‘α’) in the setting of first-order logics. Despite well-known results by Montague and by Thomason that claim otherwise, any of the so-called “modal” logics of knowledge and belief can be compiled into classical first-order logics that have a corresponding predicate on sentences. Moreover, through the use of a partial truth predicate, the standard modal axiom schemata can be translated into single sentences, making it possible to use conventional first-order logic theorem provers to directly derive results in a wide class of modal logics.
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    Oxford, UK : Blackwell Publishing Ltd
    Computational intelligence 4 (1988), S. 0 
    ISSN: 1467-8640
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Notes: The Graph Theorist, GT, is a system that performs mathematical research in graph theory. From the definitions in its input knowledge base, GT constructs examples of mathematical concepts, conjectures and proves mathematical theorems about concepts, and discovers new concepts. Discovery is driven both by examples and by definitional form. The discovery processes construct a semantic net that links all of GT's concepts together.Each definition is an algebraic expression whose semantic interpretation is a stylized algorithm to generate a class of graphs correctly and completely. From a knowledge base of these concept definitions, GT is able to conjecture and prove such theorems as “The set of acyclic, connected graphs is precisely the set of trees” and “There is no odd-regular graph on an odd number of vertices.” GT explores new concepts either to develop an area of knowledge or to link a newly acquired concept into a pre-existing knowledge base. New concepts arise from the specialization of an existing concept, the generalization of an existing concept, and the merger of two or more existing concepts. From an initial knowledge base containing only the definition of “graph,” GT discovers such concepts as acyclic graphs, connected graphs, and bipartite graphs.
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    Expert systems 5 (1988), S. 0 
    ISSN: 1468-0394
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Notes: Abstract: The Trainee Teacher Support System (TTSS) is a computer based advisory system for trainee teachers. Development work, in the form of a feasibility study, has been conducted over the past three years. The main purpose of this study is to investigate the application of expert systems technology and artificial intelligence techniques to the formalisation of experienced teachers’ knowledge of classroom practice. The domain chosen is that of the school based ‘teacher-tutor’, responsible for guiding and advising the trainee teacher. The TTSS embodies a model of processes which underly classroom events. It has a knowledge base of rules, accumulates a database of facts and has a rule implementation program. It is undergoing continued development in order to capture the teacher-tutor's understanding of classroom dynamics on a finer timescale.
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    Expert systems 5 (1988), S. 0 
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    Expert systems 5 (1988), S. 0 
    ISSN: 1468-0394
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    Topics: Computer Science
    Notes: Abstract: The domain of mathematics has played a special part in the evolution of Intelligent Tutoring Systems (ITSs), beginning as far back as the 1950s when conventional Computer Assisted Instruction (CAI) came into being. A brief historical review of this evolutionary process is presented, followed by a selective survey of some of the intelligent tutoring systems in the mathematics domain as well as some of their shortcomings and the criticisms levelled against them. The work achieved so far towards the realisation of an intelligent tutoring system for a complex mathematical domain is presented. A major conclusion is that the ‘mal-rule’ methodology for developing tutoring systems may lend itself to simple ‘primitive’ domains, but its credibility is seriously questioned when it is applied to more ‘complex’ domains. An alternative methodology is proposed to solve this problem, together with an illustration.
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    Expert systems 5 (1988), S. 0 
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    Expert systems 5 (1988), S. 0 
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    Topics: Computer Science
    Notes: FIRST CLASS is an inductive expert system development tool written by William Hapgood and supplied by 1 st-Class Expert Systems Inc. The product runs on IBM PC, XT and AT computers and close compatibles, running MS/DOS 2.0 or higher. It is sold in two versons, 1st-Class (at $495 U.S.) and 1st-Class Fusion (at $1295). This is a review of the plain version; but mention of ‘Fusion’ facilities is made where appropriate. 1st-Class Expert Systems Inc. can be contacted at: 286 Boston Post Road, Wayland, Massachusetts 1778, USA (617 358–7722).
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    Expert systems 5 (1988), S. 0 
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    Notes: Abstract: To overcome the inefficiency of domain independent tools, a domain-specific knowledge-based shell for parallel machine scheduling problems, PAMS (PArallel Machine Scheduling System), is proposed. PAMS has the following features; mixed knowledge representation, two-stage status-driven control strategy, conflict resolution using domain theory, domain-specific syntax and primitive operators, interface with database, domain-specific input/output interface, interactive scheduling capability, built-in heuristic knowledge, multiple levels of schedule, and expansibility of the domain. A prototype of PAMS, PAMS-1, is developed using C-language on a supermicrocomputer, and the performance of PAMS-1 is evaluated. The results show that the PAMS-1 performs very well from various perspectives.
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    Expert systems 5 (1988), S. 0 
    ISSN: 1468-0394
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    Topics: Computer Science
    Notes: Abstract: A system for the generation of naval flying programmes is described. The task is typical of some resource allocation problems, and comprises both the allocation of airborne resources to naval activities whilst taking into account a number of constraints, and the re-allocation of these resources when circumstances change whilst retaining as much of the original plan as possible. Techniques for constraint-based reasoning and assumption-based reasoning are combined to solve the task. An algorithm is described, based around an Assumption-Based Truth Maintenance System (ATMS), that is able to generate an initial allocation, determine the knock-on effects of changing requirements or resources, to retain those parts of the plan that were unaffected, and to re-allocate those parts that were affected. An interactive graphical interface has been designed that allows the user and the system to cooperate in the creation of flying programmes that meet the constraints and fit the situation at hand.
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    Expert systems 5 (1988), S. 0 
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    Topics: Computer Science
    Notes: Abstract: This is a review of Expert Systems (ES) in the finance and banking areas. Their purpose, mode of operation and some design issues are discussed. This overview also looks at the most advanced research developments concerning strategic business planning, management, negotiation, and the use of qualitative reasoning for corporate assessment.
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    Expert systems 5 (1988), S. 0 
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    Notes: Abstract: The integration of a simulation model with two expert systems is described. The first expert system is the front end of the Hybrid Expert Simulation System (HESS) and is designed to check the consistency of the input variables which are provided to the simulation model by the end user. The second expert system is the back end of HESS and is designed to make recommendations based on experimentations with the simulation model. A case study for a software development life cycle process is described.
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    Expert systems 5 (1988), S. 0 
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    Expert systems 5 (1988), S. 0 
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    Expert systems 5 (1988), S. 0 
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    Expert systems 5 (1988), S. 0 
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    Computational intelligence 4 (1988), S. 0 
    ISSN: 1467-8640
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Notes: We examine a number of logics of knowledge and belief from the perspective of knowledge-based systems. We are concerned with the beliefs of a knowledge-based system, including both the system's base set of beliefs–those garnered directly from the world–and beliefs that follow from the base set. Three things to consider with such logics are the expressive power of the language of the logic, the correctness and completeness of the inferences sanctioned, and the speed with which it is possible to determine whether a given sentence is believed. The influential possible worlds approach to representing belief has the property of logical omniscience, which makes for inferences that are unacceptable in the context of belief and may take too much time to make. We examine a number of weak logics which attempt to deal with these problems. These logics divide into three categories: those that admit incomplete or inconsistent situations into their semantics, those that posit a number of distinct states for a believer which correspond roughly to frames of mind, and those that incorporate axioms or other syntactic entities directly into the semantics. As to expressive power, we consider whether belief should be represented by a predicate or a sentential operator and examine the boundary between self-referential and inconsistent systems. Finally, we consider logics of believing only, which add the assumption that a system's base set of beliefs are, in a certain sense, all that it believes.
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    Computational intelligence 4 (1988), S. 0 
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    Topics: Computer Science
    Notes: The theory of evidence proposed by G. Shafer is gaining more and more acceptance in the field of artificial intelligence, for the purpose of managing uncertainty in knowledge bases. One of the crucial problems is combining uncertain pieces of evidence stemming from several sources, whether rules or physical sensors. This paper examines the framework of belief functions in terms of expressive power for knowledge representation. It is recalled that probability theory and Zadeh's theory of possibility are mathematically encompassed by the theory of evidence, as far as the evaluation of belief is concerned. Empirical and axiomatic foundations of belief functions and possibility measures are investigated. Then the general problem of combining uncertain evidence is addressed, with focus on Dempster rule of combination. It is pointed out that this rule is not very well adapted to the pooling of conflicting information. Alternative rules are proposed to cope with this problem and deal with specific cases such as nonreliable sources, nonexhaustive sources, inconsistent sources, and dependent sources. It is also indicated that combination rules issued from fuzzy set and possibility theory look more flexible than Dempster rule because many variants exist, and their numerical stability seems to be better.
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    Computational intelligence 4 (1988), S. 0 
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    Computational intelligence 4 (1988), S. 0 
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    Topics: Computer Science
    Notes: McDermott has recently explained his fundamental philosophical shift on the methodology of artificial intelligence (AI) and has further suggested that the shift is both necessary and inevitable. The shift results from a perception that a trend towards overformalisation has detached the real problems from the research results. McDermott's criticism is an enlightened exhumation of the criticisms of the seventies and explains new ways in which the logical methodology can be abused. I argue that McDermott's criticism should not discourage the use of logic, but force a timely reexamination of its fundamental role in AI.
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    Computational intelligence 4 (1988), S. 0 
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    Topics: Computer Science
    Notes: This paper describes a planning architecture that supports a form of hierarchical planning well suited to applications involving deadlines, travel time, and resource considerations. The architecture is based upon a temporal database, a heuristic evaluator, and a decision procedure for refining partial plans. A partial plan consists of a set of tasks and constraints on their order, duration, and potential resource requirements. The temporal database records the partial plan that the planner is currently working on and computes certain consequences of that information to be used in proposing methods to further refine the plan. The heuristic evaluator examines the space of linearized extensions of a given partial plan in order to reject plans that fail to satisfy basic requirements (e.g., hard deadlines and resource limitations) and to estimate the utility of plans that meet these requirements. The information provided by the temporal database and the heuristic evaluator is combined using a decision procedure that determines how best to refine the current partial plan. Neither the temporal database nor the heuristic evaluator is complete and, without reasonably accurate information concerning the possible resource requirements of the tasks in a partial plan, there is a significant risk of missing solutions. A specification language that serves to encode expectations concerning the duration and resource requirements of tasks greatly reduces this risk, enabling useful evaluations of partial plans. Details of the specification language and examples illustrating how such expectations are exploited in decision making are provided.
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    Notes: I agree that probability in some, possibly disguised, form is a necessary component of practical inference. Our goal, therefore, must be to find how to make probability practical. Normatively motivated thinking (which includes textbook Bayesianism) is, however, mute on two topics that are crucial to practicality: the choice of a limited but useful set of initial hypotheses and the choice of decision rules. The best way of reducing the computational demands of probability is to use the smallest and simplest set of hypotheses, and the crudest decision rules that are compatible with your application's goals. Learning how to make these choices is an empirical, not a normative, endeavour.
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    Notes: This essay addresses a number of issues centered around the question of what is the best method for representing and reasoning about common sense (sometimes called plausible inference). Drew McDermott has shown that a direct translation of commonsense reasoning into logical form leads to insurmountable difficulties, from which McDermott concluded that we must resort to procedural ad hocery. This paper shows that the difficulties McDermott described are a result of insisting on using logic as the language of commonsense reasoning. If, instead, (Bayesian) probability is used, none of the technical difficulties found in using logic arise. For example, in probability, the problem of referential opacity cannot occur and nonmonotonic logics (which McDermott showed don't work anyway) are not necessary. The difficulties in applying logic to the real world are shown to arise from the limitations of truth semantics built into logic–probability substitutes the more reasonable notion of belief. In Bayesian inference, many pieces of evidence are combined to get an overall measure of belief in a proposition. This is much closer to commonsense patterns of thought than long chains of logical inference to the true conclusions. Also it is shown that English expressions of the “IF A THEN B” form are best interpreted as conditional probabilities rather than universally quantified expressions. Bayesian inference is applied to a simple example of linguistic information to illustrate the potential of this type of inference for AI. This example also shows how to deal with vague information, which has so far been the province of fuzzy logic. It is further shown that Bayesian inference gives a theoretical basis for inductive inference that is borne out in practice. Instead of insisting that probability is the best language for commonsense reasoning, a major point of this essay is to show that real inference is a complex interaction between probability, logic, and other formal representation and reasoning systems.
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    Notes: We have developed a prototype of a question-answering system which is intended to interact with an untrained user to give him information about the Yellow Pages of the French phone directory. We don't detail here the description of the system, because it is done in another paper in the same issue: “A question-answering system for the French Yellow Pages”.In this paper we first present a typology of the different kinds of unforeseen situations the system may have to handle while interacting with an untrained user. Then, we detail different strategies we have developed to solve these problems, more specifically to correct misspelt words and to deal with the properly typed, but unknown, words. These mechanisms have been integrated into the parser, and try to maintain, as long as possible, its determinism.
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    Notes: We discuss some points on which we agree, and others on which we disagree, with Cheeseman's target article. Particular agreements include the need for an eclectic approach; disagreements include the misleading distinction between probabilistic and logical reasoning regarding the notion of truth, and also some matters of nonmonotonicity.
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    Notes: This short text introduces this special issue of Computational Intelligence on artificial intelligence in France. After a brief presentation of the structure and the research activities in artificial intelligence in France, we introduce the papers enclosed herein.
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    Notes: We discuss several features of concepts used for common knowledge and argue that these features are not superficial, lexical level language-dependent issues, but deep characteristics of the knowledge itself. It is thus necessary to build knowledge representation systems compatible with these characteristics.We show that the most common suggestions to cope with typicality (e.g., many-valued and (or) nonmonotonic systems) fail to capture entirely this phenomenon. As for the other features, no serious attempt has been made yet, and we only propose tentative elements for a solution.The main idea is to decouple the notion of concept from the notion of basic element (predicate, node), and to represent a concept by an open-ended family of entities of the system. Each entity conveys a possible interpretation of the concept, and interpretations are ordered, according to their “depth.” An example illustrating the main features of this scheme is provided.
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    Notes: This article provides a brief account with sketchy technical details of the major directions in machine learning research done at the Laboratoire de recherche en informatique (LRI) at Orsay University in France. References contain publications giving details on the projects described in this paper and on closely related works.Our research has several objectives: looking for a sound basis of the process of generalization from examples, using this to study conceptual clustering with automatic synthesis of descriptors; studying the nature and goodness of an explanation in the context of apprentice systems; and developing experimental learning systems based on these principles applied to various practical domains. The approach taken by our research group has evolved with time but is still mainly based on learning of concepts from examples using logic representations and techniques. It corresponds to a major goal of our group: to give a clear and rigorous picture, if not a theory, of the topics under investigation. Several aspects are persued at the same time: concept learning by generalization, developments of explanation-based learning techniques, analogy reasoning, and automatic tuning of the description language. These different directions are related to or stimulated by different domains of tasks: learning of rule bases, games, computer-aided teaching, learning in noisy environments, and so on. They are described in this article in the light of the main directions. The goal of a complete universal integrated system is still a far cry ahead, but as states a famous Chinese proverb: “The end lies in the way”.
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    Notes: In the following paper we analyze Reiter's default logic and suggest modifying the notion of an extension for default theories. This modification leads to two important properties which are not guaranteed in Reiter's formalism: the existence of extensions and semimonotonicity.
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    Notes: This paper describes a uniform formalization of much of the current work in artificial intelligence on inference systems. We show that many of these systems, including first-order theorem provers, assumption-based truth maintenance systems (atmss), and unimplemented formal systems such as default logic or circumscription, can be subsumed under a single general framework.We begin by defining this framework, which is based on a mathematical structure known as a bilattice. We present a formal definition of inference using this structure and show that this definition generalizes work involving atmss and some simple nonmonotonic logics.Following the theoretical description, we describe a constructive approach to inference in this setting; the resulting generalization of both conventional inference and atmss is achieved without incurring any substantial computational overhead. We show that our approach can also be used to implement a default reasoner, and discuss a combination of default and atms methods that enables us to formally describe an “incremental” default reasoning system. This incremental system does not need to perform consistency checks before drawing tentative conclusions, but can instead adjust its beliefs when a default premise or conclusion is overturned in the face of convincing contradictory evidence. The system is therefore much more computationally viable than earlier approaches.Finally, we discuss the implementation of our ideas. We begin by considering general issues that need to be addressed when implementing a multivalued approach such as that we are proposing, and then turn to specific examples showing the results of an existing implementation. This single implementation is used to solve a digital simulation task using first-order logic, a diagnostic task using atmss as suggested by de Kleer and Williams, a problem in default reasoning as in Reiter's default logic or McCarthy's circumscription, and to solve the same problem more efficiently by combining default methods with justification information. All of these applications use the same general-purpose bilattice theorem prover and differ only in the choice of bilattice being considered.
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    Notes: An architecture for a rational agent must allow for means-end reasoning, for the weighing of competing alternatives, and for interactions betwen these two forms of reasoning. Such an architecture must also address the problem of resource boundedness. We sketch a solution of the first problem that points the way to a solution of the second. In particular, we present a high-level specification of the practical-reasoning component of an architecture for a resource-bounded rational agent. In this architecture, a major role of the agent's plans is to constrain the amount of further practical reasoning she must perform.
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    Notes: Correct conventional nonlinear planners operate in accordance with Chapman's modal truth criterion (MTC). The MTC characterizes the conditions under which an assertion will be true at a point in a nonlinear plan. However, the MTC is not all one requires in order to build a realistic planning system: it merely sanctions the use of a number of plan modifications in order to achieve each assertion in a developing plan. The number of modifications that can be made is usually very large. To avoid breadth-first search a planner must have some idea of which plan modification to consider. We describe a domain-independent search heuristic called temporal coherence, which helps guide the search through the space of partial plans defined by the MTC. Temporal coherence works by suggesting certain orderings of goal achievement as more appealing than others, and thus by finding bindings for plan variables consistent with the planner's overall goals. Our experience with a real nonlinear planner has highlighted the need for such a heuristic. In this paper, we give an example planning problem and use it to illustrate how temporal coherence can speed the search for an acceptable plan. We also prove that if a solution exists in the partial plan search space defined by the MTC, then there exists a path to that solution which is sanctioned by temporal coherence.
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    Notes: This paper presents the GEM concurrency model and GEMPLAN, a multiagent planner based on this model. Unlike standard state-based AI representations, GEM is unique in its explicit emphasis on events and domain structure. In particular, a world domain is modeled as a set of regions composed of interrelated events. Event-based temporal-logic constraints are then associated with each region to delimit legal domain behavior. The GEMPLAN planner directly reflects this emphasis on domain structure and constraints. It can be viewed as a general-purpose constraint satisfaction facility which constructs a network of interrelated events (a “plan”) that is subdivided into regions (“subplans”), satisfies all applicable regional constraints, and also achieves some stated goal.GEMPLAN extends and generalizes previous planning architectures in the range of constraint forms it handles and in the flexibility of its constraint satisfaction search strategy. One critical aspect of our work has been an emphasis on localized reasoning—techniques that make explicit use of domain structure. For example, GEM localizes the applicability of domain constraints and imposes additional “locality constraints” on the basis of domain structure. Together, constraint localization and locality constraints provide semantic information that can be used to alleviate several aspects of the frame problem for multiagent domains. The GEMPLAN planner reflects the use of locality by subdividing its constraint satisfaction search space into regional planning search spaces. Utilizing constraint and property localization, GEMPLAN can pinpoint and rectify interactions among these regional search spaces, thus reducing the burden of “interaction analysis” ubiquitous to most planning systems. Because GEMPLAN is specifically geared towards parallel, multiagent domains, we believe that its natural application areas will include scheduling and other forms of organizational coordination.
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    Notes: This paper presents a method of solving planning problems that involve actions whose effects change according to the situations in which they are performed. The approach is an extension of the conventional planning methodology in which plans are constructed through an iterative process of scanning for goals that are not yet satisfied, inserting actions to achieve them, and introducing subgoals to these actions. This methodology was originally developed under the assumption that one would be dealing exclusively with actions that produce the same effects in every situation. The extension involves introducing additional subgoals to actions above and beyond the preconditions of execution normally introduced. These additional subgoals, called secondary preconditions, ensure that the actions are performed in contexts conducive to producing the effects we desire. This paper defines and analyzes secondary preconditions from a mathematically rigorous standpoint and demonstrates how they can be derived from regression operators.
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    Notes: Reasoning about actions necessarily involves tracking the truth of assertions about the world over time. The SIPE planning system retains the efficiency of the STRIPS assumption for this while enhancing expressive power by allowing the specification of a causl theory. Separation of knowledge about causality from knowledge about actions relieves operators of much of their representational burden and allows them to be applicable in a wide range of contexts. The implementation of causal theories is described, together with examples and evaluations of the system's expressive power and efficiency.
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    Notes: Abstract: Knowledge based systems offer considerable potential for the creation of new learning environments. In education such environments can be used with the mediation of a teacher and limits to the interpretation of the knowledge do not necessarily present problems. Intelligent tutoring systems cannot rely on human mediation and all interpretation of learner understanding is restricted to semantics of the knowledge representation. Thus the choice of representation is fundamental to the design of an intelligent tutoring system. Experience from an engineering context suggests that the success of a few intelligent tutoring systems depends on the formal nature of the topics considered. Typical topics for education and training require the integration of a formal understanding with an informal interpretation of considerable complexity. A new approach to the use of knowledge based systems, firmly centred on experience of applications actively used in education and/or training, will be required to solve this problem.
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    Notes: Abstract: The article summarises the results of a five year research programme aimed at the creation and development of a prototype ‘intelligent authoring system’(IAS)—that is. a system for authoring software that stimulates the skills and knowledge of a conventional Computer Assisted Learning authoring team, thus allowing a computer-naive author to create a working program interactively without the need for human assistance. We argue that a knowledge representation in the form of ‘event schema’ or 'script’ for each of the common types of educational software is ideally suited to meeting our five main criteria for IAS development, and present a brief of overview of the SCALD’(Scriptal CAL Designer) prototype IAS. The current version of the system is implemented in Prolog on an Apple Macintosh micro, and is capable of creating a range of educational programs of either ‘an instructional’ type or a 'science demonstration’ type. We believe that scripts could be produced fairly easily for most other types of program design and are currently working on a hybrid ‘instructional-demonstration’ script and an ‘adventure-game’ script. The main strengths and weaknesses of the Scald system are discussed, and suggestions made for further developments.
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    Notes: Abstract: Most existing expert systems store rules which guide programme behaviour. Inductive expert systems generate rules from properly formatted descriptions of historical data. The ID/3 algorithm, based on Earl Hunt's Concept Learning System, is among the more popular induction algorithms for this application. A general description of ID/3 is given along with suggestions for further possible refinements of the algorithm. Because ID/3 uses decision trees to store knowledge and does not inherently exclude the application of weights to paths through the tree, the algorithm bears a remarkable conceptual resemblance to neural networks. From this analogy some new applications for the algorithm are derived.
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    Notes: Abstract: Knowledge acquisition has long been considered to be the major constraint in the development of expert systems. Conventional wisdom also maintains that the major problem encountered in knowledge acquisition is in identifying the varying structures and characteristics of domain knowledge and matching these to suitable acquisition techniques. With the aid of the first substantial systematic analysis of a sample of expert systems applications developed in the real world, the authors describe what is actually going on in terms of knowledge acquisition. In the light of the evidence, it is argued that a reappraisal of the conventional approach to knowledge acquisition is necessary.
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    Notes: Abstract: In the early 1970s, research into Artificial Intelligence (Al) in Britain was almost wiped out following the publication of an unfavourable report to government. In the 1980s, Al emerged from obscurity with Expert Systems as its leading edge and has now become the focus of considerable activity with an ever-growing volume of practical applications developed or under development in British industry and business. This paper reviews the growth of business interest in Expert Systems from a British perspective and surveys the principal work carried out to date. Technical issues highlighted by this work are considered and prospects for future development are discussed.
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    Notes: Abstract The ‘Knowledge Engineer's Assistant’ (KEATS) is a software environment suitable for constructing knowledge-based systems. In this paper, we discuss its role in supporting the knowledge engineer in the tasks of knowledge elicitation and domain understanding. KEATS is based upon our own investigations of the behaviour and needs of knowledge engineers and provides two enhancements to other modern ‘shells’. ‘toolkits’, and ‘environments’ for knowledge engineering: (i) transcript analysis facilities, and (ii) a sketchpad on which the KE may draw a freehand representation of the domain, from which code is automatically generated. KEATS uses a hybrid representation formalism that includes a frame-based language and a rule interpreter. We describe the novel components of KEATS in detail, and present an example of how KEATS was used to build an electronic fault diagnosis system.
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    Expert systems 5 (1988), S. 0 
    ISSN: 1468-0394
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
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  • 90
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    Topics: Computer Science
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  • 91
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    Expert systems 5 (1988), S. 0 
    ISSN: 1468-0394
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Notes: Abstract: This paper is concerned with structural models of what have come to be called Intelligent CAL systems. It proposes and examines such models in the light of the needs of different types of CAL systems, particularly those systems which offer learner control. Based on the five-circle model proposed by Tim O’ Shea and others, a more general ‘figure of eight’ model is put forward which accords with certain of the ideas suggested by Gordon Pask concerning the architecture of learning systems.
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  • 92
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    Expert systems 5 (1988), S. 0 
    ISSN: 1468-0394
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
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  • 93
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    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Notes: Abstract: Two types of expert system which involve statistical expertise are statistical consulting programs and programs which find patterns in databases. Consulting programs can now be built quickly using programming tools. Most expert systems include mechanisms for reasoning under uncertainty. Methods under investigation include fuzzy logic, Dempster-Shafer theory, Bayesian analysis and various ad hoc methods. Learning systems use statistics to infer inductive rules, and statistical reasoning can also be used to evaluate the performance of expert systems. The use of a prototype statistical expert system, XSAMPLE, is demonstrated, as a system to handle a consulting session with a statistically moderately advanced user.
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  • 94
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  • 95
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  • 96
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    Expert systems 5 (1988), S. 0 
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    Expert systems 5 (1988), S. 0 
    ISSN: 1468-0394
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Notes: Leonardo is an expert system development tool supplied by Creative Logic Ltd. The product runs on IBM XT or AT personal computers or close compatibles. Leonardo is available in three levels, each incorporating additional facilities. Level 1 costs £149, level 2 costs £695 and level 3 costs £1,995. A VAX version is also on sale at between £4,000 and £12,000, depending on machine configuration. Creative Logic Ltd. can be contacted at: Brunel Science Park, Kingston Lane, Uxbridge, Middlesex UB8 3PQ (0895 74468). (The version reviewed in this article was release 3.00, level 3, for the PC. It was run on a Tandon PCX with 640K bytes RAM, a 20-megabyte hard disc and a monochrome monitor.)
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    Springer
    Mathematical programming 42 (1988), S. 363-374 
    ISSN: 1436-4646
    Keywords: Newton method ; parallel algorithms ; superlinear convergence
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science , Mathematics
    Notes: Abstract A parallel Newton method is described for the minimization of a twice continuously differentiable uniformly convex functionF(x). The algorithm generates a sequence {x j } which converges superlinearly to the global minimizer ofF(x).
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    Mathematical programming 42 (1988), S. 489-563 
    ISSN: 1436-4646
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science , Mathematics
    Notes: Abstract Polyhedra related to matroids and sub- or supermodular functions play a central role in combinatorial optimization. The purpose of this paper is to present a unified treatment of the subject. The structure of generalized polymatroids and submodular flow systems is discussed in detail along with their close interrelation. In addition to providing several applications, we summarize many known results within this general framework.
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    Mathematical programming 42 (1988), S. 113-123 
    ISSN: 1436-4646
    Keywords: Scheduling ; large-scale 0–1 model ; variable fixing ; coefficient reduction ; special ordered sets
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science , Mathematics
    Notes: Abstract In this work an extension of the Beale-Tomlin special ordered sets is introduced that has proved to be efficient for solving certain types of open shop scheduling problems. Besides their usual characteristics, exclusivity constraints in the jobs are allowed, more general than tree-like precedence structures are considered, and semi-active schedules that cannot be labeled as non-optimal solutions may occur. The problem is formulated as a large-scale 0–1 model. Computational experience on some real-life problems is reported.
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