bluuebunny/crossref_metadata_2025 huggingface dataset:
Determining intended evidence relations in natural language arguments
Authors: YOUNG MARK A. , COHEN ROBIN
Published: April 2007

When trying to understand a speaker's argument, it is necessary to determine what her claim is and what evidence she provides for it. It is necessary, therefore, to be able to recognize evidence relations in terms of the speaker's beliefs. This paper describes an implementation of anevidence oracle, which tests for evidence between statements and builds a model of the speaker based on the evidence relations found. This implementation is intended to be an advance in the development of practical discourse analysis systems, proposing a basis for verifying certain relationships between utterances. Another contribution of the work is a stratified speaker model which allows for varying levels of acceptance of beliefs attributed to the speaker. Integration of the implemented evidence oracle into a full discourse analyser is presented, together with output illustrating the analysis for several sample arguments. Some extensions of this approach for plan inference are also discussed.

Lorsque l'on essaie de comprendre l'argument d'un locuteur, il importe de déterminer la nature de sa prétention et le type d'évidence qui l'accompagne. Par conséquent, il est nécessaire de pouvoir distinguer des relations d'évidence les croyances du locuteur. Cet article décrit la mise en oeuvre d'un oracle qui recherche l'évidence entre des énoncés et construit un modèle du locuteur en fonction des relations d'évidence constatées. Cette mise en oeuvre propose une base pour vérifier certaines relations entre des énoncés; elle se veut une contribution au développement d'un système pratique d'analyse du discours. Une autre contribution de cette recherche est l'élaboration d'un modèle de locuteur stratifyé qui tient compte de niveaux variables d'acceptation des croyances attributeés au locuteur. l'intégration de l'oracle d'évidence sous forme d'analyseur de discours est présentée, ainsi que des illustrations de l' analyse de plusieurs arguments types. Une extension de cette approche à l'inférence de plans est également discutée.
Making default inferences from logic programs
Authors: Li Liwu , YOU JIA‐HUAI
Published: April 2007

The relationship between Reiter's default logic and general logic programs, which may contain negative subgoals in rule bodies, has been discussed in the literature by translating logic programs to default logic theories. Here, we present a method to translate some default logic theories to general logic programs, and study the extensions of default logic theories with the stable model semantics of logic programming. Based on the translation method, we show that another semantics of logic programming, the well‐founded semantics, can be used to define a new version of default logic, which is more cautious than the original one. This enables the existing proof procedures for the well‐founded semantics to perform default inference. We also study the property of cumulative monotonicity for both default logic theories and general logic programs under the two different semantics. As a direct application of the translation method, logic programs can be used to make default inference for semantic networks with exceptions.

La relation entre la logique par défaut de Reiter et les programmes logiques généraux, qui peuvent comporter des sous‐buts négatifs dans les ensembles de règies, a déjàété discutée en traduisant les programmes logiques en théories de la logique par défaut. Dans cet article, les auteurs proposent une méthode pour traduire certaines théories de la logique par defaut en programmes logiques généraux et étudient les extensions des theories de la logique par defaut avec la sémantique de modéle stable de la programmation logique. En se basant sur la méthode de traduction, les auteurs démontrent qu'une autre sémantique de la programmation logique, la sémantique bien fondée, peut ětre utilisée pour définir une nouvelle version de la logique par défaut, qui est plus prudente que la première. Cela permet aux procédures de preuve existantes de la sémantique bien fondée d' effectuer l' inférence par défaut. Les auteurs examinent également les caracteristiques de la monotonicité cumulative pour les theories de la logique par défaut et les programmes logiques généraux selon les deux différentes sémantiques. Une application directe de la méthode de traduction est la possibilityé d' utiliser les programmes logiques pour effectuer de l' inférence par défaut pour les réseaux sémantiques avec exceptions.
Uncertainty, belief, and probability1
Authors: FAGIN RONALD , HALPERN JOSEPH Y.
Published: April 2007

We introduce a new probabilistic approach to dealing with uncertainty, based on the observation that probability theory does not require that every event be assigned a probability. For anonmeasurableevent (one to which we do not assign a probability), we can talk about only theinner measureandouter measureof the event. In addition to removing the requirement that every event be assigned a probability, our approach circumvents other criticisms of probability‐based approaches to uncertainty. For example, the measure of belief in an event turns out to be represented by an interval (defined by the inner and outer measures), rather than by a single number. Further, this approach allows us to assign a belief (inner measure) to an eventEwithout committing to a belief about its negation‐E(since the inner measure of an event plus the inner measure of its negation is not necessarily one). Interestingly enough, inner measures induced by probability measures turn out to correspond in a precise sense to Dempster‐Shafer belief functions. Hence, in addition to providing promising new conceptual tools for dealing with uncertainty, our approach shows that a key part of the important Dempster‐Shafer theory of evidence is firmly rooted in classical probability theory.

Cet article présente une nouvelle approche probabiliste en ce qui concerne le traitement de l'incertitude; celle‐ci est basée sur l'observation que la théorie des probabilityés n'exige pas qu'une probabilityé soit assignée à chaque événement. Dans le cas d'un événementnon mesurable(un événement pour lequel on n'assigne aucune probabilityé), nous ne pouvons discuter que de lamesure intérieureet de lamesure extérieurede l'évenément. En plus d'éliminer la nécessité d'assigner une probabilityéà l'événement, cette nouvelle approche apporte une réponse aux autres critiques des approches à l'incertitude basées sur des probabilityés. Par exemple, la mesure de croyance dans un événement est représentée par un intervalle (défini par la mesure intérieure et extérieure) plutǒt que par un nombre unique. De plus, cette approche nous permet d'assigner une croyance (mesure intérieure) à un événementEsans se compromettre vers une croyance à propos de sa négation‐E(puisque la mesure intérieure d'un événement et la mesure intérieure de sa négation ne sont pas nécessairement une seule et unique mesure). II est intéressant de noter que les mesures intérieures qui résultent des mesures de probabilityé correspondent d'une manière précise aux fonctions de croyance de Dempster‐Shafer. En plus de constituer un nouvel outil conceptuel prometteur dans le traitement de l'incertitude, cette approche démontre qu'une partie importante de la théorie de l'évidence de Dempster‐Shafer est fermement ancrée dans la theorie classique des probabilityés.
From functional specification to syntactic structures: systemic grammar and tree adjoining grammar
Authors: Yang Gijoo , McCoy Kathleen F. , Vijay‐Shanker K.
Published: April 2007

In this paper we provide an implementation strategy to map a functional specification of an utterance into a syntactically well‐formed sentence. We do this by integrating the functional and the syntactic perspectives on language, which we take to be exemplified by systemic grammars and tree adjoining grammars (TAGs) respectively. From systemic grammars we borrow the use of networks of choices to classify the set of possible constructions. The choices expressed in an input are mapped by our generator to a syntactic structure as defined by a TAG. We argue that the TAG structures can be appropriate structural units of realization in an implementation of a generator based on systemic grammar and also that a systemic grammar provides an effective means of deciding between various syntactic possibilities expressed in a TAG grammar. We have developed a generation strategy which takes advantage of what both paradigms offer to generation, without compromising either.
On the need for domain communication knowledge
Authors: Kittredge Richard , Korelsky Tanya , Rambow Owen
Published: April 2007

Much research in text planning has been oriented towards identifying the rhetorical component of communication knowledge that allows for the structuring of coherent multi‐sentential or even multi‐paragraph text. However, several researchers have recently found rhetoric‐based top‐down approaches to be inadequate for their particular needs. In this paper, we explore the issue by introducing the concept of “domain communication knowledge” as a new analytical tool. By analyzing two existing rhetoric‐based text planners, and by closely analyzing a particular genre, namely reports, we conclude that domain‐specific knowledge about communication is pervasive and should be represented explicitly for the text planning task.

La plupart des travaux de recherche dans la planification de textes ont été orientés vers ľ identification de la composante rhétorique de la connaissance de la communication, qui permet de structurer de manière cohérente un texte à phrases ou à paragraphes multiples. ?autre part, plusieurs chercheurs ont récemment constaté que les approches descendantes basées sur la rhétorique ne convenaient pas à leurs besoins particuliers. Dans cet article, les auteurs examinent la question en utilisant un nouvel outil analytique, soit le concept de 〈〈 connaissance du domaine reliée à la communication 〉〉 En étudiant deux planificateurs de textes existants et an analysant de très près un genre particulier, soit des rapports, les auteurs concluent que la connaissance spécifique du domaine à propos de la communication est subtile et devrait faire ľobjet ?une representation explicite pour la planification de textes.
STORY GENERATION BASED ON DYNAMICS OF THE MIND
Authors: Okada Naoyuki , Endo Tsutomu
Published: April 2007

A story generation system based on dynamics of the mind is presented. Semantic theories until now avoided discussing a linkage of language with encyclopedic human knowledge. This paper attacks the problem of how to make clear the complicated, wide‐ranging dynamics of the mind and how to connect it to language.

First, the background of this study is shown, in which our model of the mind, with both five levels along the concept formation process and eight domains according to the contents of mental activities, is surveyed.

Based on this model, then, the dynamics of mind are discussed, along an Aesop fable. A unit of data processing in the mind is called a “module,” and the mental dynamics are considered as a chain activation of those modules, represented by a dynamic network. Next, a method for story generation is discussed. Propositional information of a sentence is embedded in a slot of activated, frame‐structured modules, and the discourse structure of a generated story basically depends on the dynamic network. Both the chain activation and the generation processes are verified by experiments.

Lastly, residual problems of our research, a comparison with related research, and its applications are discussed.

This case study would be expected to give a basis to integrated systems for problem solving, natural language and image understandings, their generations, and intelligent robots.
PROLEGOMENA TO ANY FUTURE QUALITATIVE PHYSICS
Authors: Sacks Elisha P. , Doyle Jon
Published: April 2007

We evaluate the success of the qualitative physics enterprise in automating expert reasoning about physical systems. The field has agreed, in essentials, upon a modeling language for dynamical systems, a representation for behavior, and an analysis method. The modeling language consists of generalized ordinary differential equations containing unspecified constants and monotonic functions; the behavioral representation decomposes the state space described by the equations into discrete cells; and the analysis method traces the transitory response using sign arithmetic and calculus. The field has developed several reasoners based on these choices over some 15 years. We demonstrate that these reasoners exhibit severe limitations in comparison with experts and can analyze only a handful of simple systems. We trace the limitations to inappropriate assumptions about expert needs and methods. Experts ordinarily seek to determine asymptotic behavior rather than transient response, and use extensive mathematical knowledge and numerical analysis to derive this information. Standard mathematics provides complete qualitative understanding of many systems, including those addressed so far in qualitative physics. Preliminary evidence suggests that expert knowledge and reasoning methods can be automated directly, without restriction to the accepted language, representation, and algorithm. We conclude that expert knowledge and methods provide the most promising basis for automating qualitative reasoning about physical systems.
A STRATEGY FOR RESEARCH ON MODEL FORMULATION
Authors: Steier David
Published: April 2007

The starting point for this commentary is Sacks’ and Doyle's conclusion that a central problem for qualitative physics is automating mathematical model formulation. We believe that model formulation is also a central problem for operations research, and although we have focused on models for production planning rather than for engineering systems analysis, our experience confirms that of Sacks and Doyle, that at least parts of model formulation are amenable to automation. In terms of their recommendations for future research, their strategy seems to emphasize the formalization of mathematical knowledge. We wish to stress that understanding the design or analysis context, the problem domain, and resource constraints on the modeling process is equally important. Methods used in cognitive psychology for understanding human problem solving, such as protocol analysis, can complement mathematical study by helping us understanding the processing that human modelers use to bring mathematical knowledge to bear. We have been using the results of such analyses to guide the creation of a model formulation system (MFS) within the Soar architecture. The use of cognitive studies and computer models in tandem seems to represent a viable strategy for making progress in this area.
DIRECTIONS FOR QUALITATIVE REASONING
Authors: Kalagnanam Jayant Are. , Simon Herbert A.
Published: April 2007

Sacks & Doyle provide an excellent overview of the fundamental limitations of the SPQR representations for reasoning about the qualitative properties of dynamic systems. We take this opportunity to outline some new directions for qualitative reasoning. In this paper, we provide a rigorous mathematical characterization for the term “qualitative property” in the context of static and dynamic systems. Based on these characterizations, we show that interval representations are well suited for reasoning about the qualitative properties of static systems such as qualitative comparative statics and qualitative stability. Moreover, we also show that symbolic computations help in the derivation of useful global properties of dynamic systems which can be used to guide numerical sampling of differential equations. The integration of symbolic and numeric methods provides a powerful approach for automating the qualitative analysis of differential equations.
PAU: PARSING AND UNDERSTANDING WITH UNIFORM SYNTACTIC, SEMANTIC, AND IDIOMATIC REPRESENTATIONS
Authors: Chin David N.
Published: April 2007

PAU is an all‐paths chart‐based unification parser that uses the same uniform representation for regular syntax, irregular syntax such as idioms, and semantics. PAU's representation has very little redundancy, simplifying the task of adding new semantics and syntax fo PAU's knowledge base. PAU uses relations between the syntax and semantics to avoid the proliferation of rules found in semantic grammars. By encoding semantics at the same level of representation as syntax, PAU is able to use semantic constraints early in the parse to eliminate semantically anomalous syntactic interpretations. Examples are given to show how PAU can handle the many eccentricities of different idioms using the same mechanisms as are used to handle regular syntax and semantics. These include the ability of some idioms, but not other idioms of the same syntactic form to undergo passivization, particle movement, action nominalization, indirect object movement, modification by adjectives, gerundive nominalization, prepositional phrase preposing, and topicalization. PAU's representation is bidirectional and is also used by a companion generator. PAU is designed to be efficient, runs in real time on typical workstations, and is being used in a number of natural language systems.
METAPHORIC COHERENCE: DISTINGUISHING VERBAL METAPHOR FROM “ANOMALY”
Authors: Russell Sylvia Weber
Published: April 2007

Theories and computational models of metaphor comprehension generally circumvent the question of metaphor versus “anomaly” in favor of a treatment of metaphor versus literal language. Making the distinction between metaphoric and “anomalous” expressions is subject to wide variation in judgment, yet humans agree that some potentially metaphoric expressions are much more comprehensible than others. In the context of a program which interprets simple isolated sentences that are potential instances of cross‐modal and other verbal metaphor, I consider some possible coherence criteria which must be satisfied for an expression to be “conceivable” metaphorically. Metaphoric constraints on object nominals are represented as abstracted or extended along with the invariant structural components of the verb meaning in a metaphor. This approach distinguishes what is preserved in metaphoric extension from that which is “violated”, thus referring to both “similarity” and “dissimilarity” views of metaphor. The role and potential limits of represented abstracted properties and constraints is discussed as they relate to the recognition of incoherent semantic combinations and the rejection or adjustment of metaphoric interpretations.
HIERARCHICAL ARC CONSISTENCY FOR DISJOINT REAL INTERVALS IN CONSTRAINT LOGIC PROGRAMMING
Authors: Sidebottom Greg , Havens William S.
Published: April 2007

There have been many proposals for adding sound implementations of numeric processing to Prolog. This paper describes an approach to numeric constraint processing which has been implemented in Echidna, a new constraint logic programming (CLP) language. Echidna uses consistency algorithms which can actively process a wider variety of numeric constraints than most other CLP systems, including constraints containing some common nonlinear functions. A unique feature of Echidna is that it implements domains for real‐valued variables with hierarchical data structures and exploits this structure using a hierarchical arc consistency algorithm specialized for numeric constraints. This gives Echidna two advantages over other systems. First, the union of disjoint intervals can be represented directly. Other approaches require trying each disjoint interval in turn during backtrack search. Second, the hierarchical structure facilitates varying the precision of constraint processing. Consequently, it is possible to implement more effective constraint processing control algorithms which avoid unnecessary detailed domain analysis. These advantages distinguish Echidna from other CLP systems for numeric constraint processing.
CONSTRUCTION OF BELIEF AND DECISION NETWORKS
Authors: Breese John S.
Published: April 2007

We describe a representation and set of inference techniques for the dynamic construction of probabilistic and decision‐theoretic models expressed as networks. In contrast to probabilistic reasoning schemes that rely on fixed models, we develop a representation that implicitly encodes a large number of possible model structures. Based on a particular query and state of information, the system constructs a customized belief net for that particular situation. We develop an interpretation of the network construction process in terms of the implicit networks encoded in the database. A companion method for constructing belief networks with decisions and values (decision networks) is also developed that uses sensitivity analysis to focus the model building process. Finally, we discuss some issues of control of model construction and describe examples of constructing networks.
THE RELATION BETWEEN ORDINAL PROBLEM SPACE SIZES AND THE MAXIMUM NUMBER OF ORDINAL CLASSIFICATION RULES
Authors: BEN‐DAVID ARIE
Published: April 2007

A method is presented of establishing bounds on the number of classification rules in such applications as credit worthiness assessment, investment decisions, premium determination, consumer choices, employee selection, and editorial preferences, to name just a few. A function that relates the maximum number of classification rules to the problem space size of such application domains is established. It is shown that in this important class of ordinal classification problems, the maximum possible number of rules is significantly lower than the relative problem space sizes. The approach grants the ability to a priori estimate worst case response time and memory requirements, and to better predict the effectiveness of knowledge acquisition efforts.
CLAUSE MANAGEMENT SYSTEMS (CMS)
Authors: KEAN ALEX , TSIKNIS GEORGE
Published: April 2007

This paper provides an extension to the study of the clause management system (CMS) proposed by Reiter and de Kleer. The CMS is adapted specifically for aiding a reasoning system in explanations generation. The reasoning system transmits propositional formulae representing its knowledge to the CMS and in return, it requests the CMS for minimal and consistent explanations of a query with respect to the CMS knowledge base. The CMS knowledge base is represented by a set of prime implicates. The classification of implicates as minimal, prime, trivial, and minimal trivial is carefully examined. Similarly, the notion of a support for a clause including minimal, prime, trivial, and minimal trivial is also elaborated. The methods to compute these supports from implicates and a preference ordering scheme expressible by logical specificity for the set of supports for a given clause are also presented. The generalization of the notion of a minimal support for a conjunction of clauses is also shown. Finally, two logic‐based diagnostic reasoning paradigms aided by the CMS are shown to exemplify the functionality of the CMS.
HYBRID ALGORITHMS FOR THE CONSTRAINT SATISFACTION PROBLEM
Authors: Prosser Patrick
Published: April 2007

It might be said that there are five basic tree search algorithms for the constraint satisfaction problem (csp), namely, naive backtracking (BT), backjumping (BJ), conflict‐directed backjumping (CBJ), backmarking (BM), and forward checking (FC). In broad terms, BT, BJ, and CBJ describe different styles of backward move (backtracking), whereas BT, BM, and FC describe different styles of forward move (labeling of variables). This paper presents an approach that allows base algorithms to be combined, giving us new hybrids. The base algorithms are described explicitly, in terms of a forward move and a backward move. It is then shown that the forward move of one algorithm may be combined with the backward move of another, giving a new hybrid. In total, four hybrids are presented: backmarking with backjumping (BMJ), backmarking with conflict‐directed backjumping (BM‐CBJ), forward checking with backjumping (FC‐BJ), and forward checking with conflict‐directed backjumping (FC‐CBJ). The performances of the nine algorithms (BT, BJ, CBJ, BM, BMJ, BM‐CBJ, FC, FC‐BJ, FC‐CBJ) are compared empirically, using 450 instances of the ZEBRA problem, and it is shown that FC‐CBJ is by far the best of the algorithms examined.
OBTAINING TREES FROM THEIR DESCRIPTIONS: AN APPLICATION TO TREE‐ADJOINING GRAMMARS
Authors: Rogers James , VIJAY‐SHANKER K.
Published: April 2007

Partial descriptions are sets of constraints which do not necessarily determine a unique object. Two related issues arise when objects arc specified by partial descriptions. The first asks whether a given partial description is satisfied by any object. The second seeks to produce, from a satisfiable description, an appropriate representative of those objects which satisfy it (where the notion of appropriate is defined by the circumstances in which the partial descriptions are employed). We explore these issues in the context of two recent proposals utilizing partial descriptions of trees in the area of tree‐adjoining grammars. One involves the use of descriptions of trees in reinterpreting TAGs as a constraint‐based formalism. In the other these descriptions are the basis of a compact representation of lexicalized TAG grammars. In this context, what counts as an appropriate representative of the set of trees which satisfy a description is a tree in that set which is minimal in the sense that every other tree in the set can be derived from it by adjunction. A partial description for which there is a unique such minimal tree will be called a quasi‐tree. Our work provides precise foundations for the use of descriptions of trees in these proposals. We formalize the notions of partial descriptions of trees and of quasi‐trees, and using this, provide a mechanism which derives, from an arbitrary description, an equivalent set of quasi‐trees. The description is satisfiable iff that set of quasi‐trees is nonempty. We then provide a second mechanism which constructs the unique minimal trees satisfying these quasi‐trees. Thus these mechanisms decide our issues in a strong way–they resolve any description into an equivalent set of descriptions which have unambiguous representative trees, and produce, from that set of descriptions, those representative trees. Such mechanisms are presupposed by the LTAG proposal, but are provided in a complete form for the first time here.
RECOGNITION CAN BE HARDER THAN PARSING
Authors: Lang Bernard
Published: April 2007

The work presented here attempts to bring out some fundamental concepts that underlie some known parsing algorithms, usually called chart or dynamic programming parsers, in the hope of guiding the design of similar algorithms for other formalisms that could be considered for describing the “surface” syntax of languages. The key idea is that chart parsing is essentially equivalent to a simple construction of the intersection of the language (represented by its grammar) with a regular set containing only the input sentence to be parsed (represented by a finite state machine). The resulting grammar for that intersection is precisely what is usually called a shared forest: it represents all parses of a syntactically ambiguous sentence. Since most techniques for processing ill‐formed input can be modeled by considering a nonsingleton regular set of input sentences, we can expect to generalize these ill‐formed input processing techniques to all parsers describable with our approach.
INCREMENTAL PARSING WITH LD/TLP‐TAGS
Authors: Poller Peter
Published: April 2007

A main purpose of natural language systems (NL‐systems) is the simulation of human speech behavior, which divides into generation and analysis, in all kinds of situations. Humans process natural language in an incremental style, which means that sentences are generated or analyzed in a piecemeal fashion. Observations show that there are bidirectional dependencies between these processes. During parsing, hypotheses for the continuation of an utterance may be generated. During generation, the output may be parsed in order to detect ambiguities. This paper presents a two‐level incremental parsing algorithm for LD/TLP‐TAGs on the basis of Earley's context‐free parser. LD/TLP‐TAG is a new extension for TAG that increases the descriptive power of the formalism without changing its generative power. Elementary rules are split into local dominance description (LD) and linear precedence rules (TLP) allowing for generalizations of ordering constraints. The presented algorithm is used within an anticipation feedback loop for the incremental syntactic generator TAG‐GEN.
TOWARD AN INTEGRATED GENERATION APPROACH WITH TREE‐ADJOINING GRAMMARS
Authors: Harbusch Karin
Published: April 2007

Natural‐language generationhas gained importance since AI systems have become more sophisticated and canned text can no longer serve the elaborate communicative tasks in such a system. In this paper, suggestions are presented to apply uniformly the formalism oftree‐adjoining grammar(TAG) for all tasks of natural‐language generation. Up to now plan‐based systems have been preferred for most of the processing during generation. Since the individual tasks of natural‐language generation are very different and complex; for example, the determination of the propositional structure of a text is described using the TAG formalism–extended byconstraintsandfeature descriptions(UCTAC). Nevertheless, this paper proposes basic ideas for the generalization of applying a grammar formalism to natural‐language generation in order to build an overall integrated system for natural‐language generation. Finally, advantages of such a uniform model are discussed.
USING UTAGS FOR INCREMENTAL AND PARALLEL GENERATION
Authors: Kilger Anne
Published: April 2007

Exploiting an incremental and parallel processing scheme is useful to improve the performance of natural language generation systems. TAG‐GEN is a TAG‐based syntactic generator that realizes both principles. It is shown how the demands of incremental and parallel generation influence the definition, the design, and the processing of syntactic rules on the basis of tree‐adjoining grammars.
THE SCOPE OF DIMENSIONAL ANALYSIS IN QUALITATIVE REASONING
Authors: Kalagnanam Jayant , Henrion Max , Subrahmanian Eswaran
Published: April 2007

Dimensional analysis, traditionally used in physics and engineering to identify quantitative relationships, has recently been applied to qualitative reasoning of physical systems. We illustrate some problems of this approach. In the light of this, we reexamine the fundamentals of dimensional analysis in order to more precisely characterize its scope and limitations as a tool in qualitative reasoning. We also explore its relationship to state equation representations of physical systems. In particular, we describe its value in providing a set of constraints to reduce the ambiguity that bedevils qualitative reasoning schemes. We argue that dimensional analysis should not be seen as a substitute for knowledge about the physics but rather a supplement to other sources of knowledge.
DEFAULT LOGICS: A UNIFIED VIEW
Authors: Froidevaux Christine , Mengin Jérôme
Published: April 2007

Default logic has been introduced for handling reasoning with incomplete knowledge. It has been widely studied, and various definitions have been proposed for it. Most of the variants have been defined by means of fixed points of some operator. We propose here another approach, which is based on a study of the way in which general rules with exceptions, used in a default reasoning process, can contradict one another. We then isolate sets of noncontradicting rules, as large as possible in order to exploit as much information as possible, and construct, for each of these sets of rules, the set of conclusions that can be deduced from it. We show that our framework encompasses most of the existing variants of default logic, allowing those variants to be compared from a knowledge representation point of view. Our approach also enables us to provide an operational definition of extensions in some interesting cases. Proof‐theoretical and semantical aspects are investigated.
A LOGICAL CHARACTERIZATION FOR TRUTH MAINTENANCE SYSTEMS WITH DEPENDENCY‐DIRECTED BACKTRACKING
Authors: Giordano Laura , Martelli Alberto
Published: April 2007

In this paper we present various logical characterizations of justification‐based (nonmonotonic) truth maintenance systems (JTMS). These characterizations, which are proved to be equivalent, aim at describing dependency‐directed backtracking (DDB) (i.e., the process of resolving conflicts which can arise when nogoods are allowed in the set of justifications), mainly relying on the intuitive idea that a contrapositrve use of justifications is needed to resolve inconsistencies. The idea is first formalized by means of the notion of three‐valued labeling and then through a transformation which explicitly adds all contrapositives of the justifications. An abductive characterization of the JTMS is provided through a further transformation which converts a set of nonmonotonic justifications to a corresponding abduction framework. This approach provides a unifying framework, based on the notion of abduction, for describing both JTMSs and assumption‐based TMSs (ATMSs).
COMPUTING PERFECT AND STABLE MODELS USING ORDERED MODEL TREES
Authors: Fernández José Alberto , Minker Jack , Yahya Adnan
Published: April 2007

Ordered model trees were introduced as a normal form for disjunctive deductive databases. They were also used to facilitate the computation of minimal models for disjunctive theories by exploiting the order imposed on the Herbrand base of the theory. In this work we show how the order on the Herbrand base can be used to compute perfect models of a disjunctive stratified finite theory. We are able to compute the stable models of a general finite theory by combining the order on the elements of the Herbrand base with previous results that had shown that the stable models of a theory T can be computed as the perfect models of a corresponding disjunctive theory ɛT resulting from applying the so called evidential transformation to T. While other methods consider many models that are rejected at the end, the use of atom ordering allows us to guarantee that every model generated belongs to the class of models being computed. As for negation‐free databases, the ordered tree serves as the canonical representation of the database.
A LOGIC OF ARGUMENTATION FOR REASONING UNDER UNCERTAINTY
Authors: Krause Paul , Ambler Simon , Elvang‐Goransson Morten , Fox John
Published: April 2007

We present the syntax and proof theory of a logic of argumentation, LA. We also outline the development of a category theoretic semantics for LA. LA is the core of a proof theoretic model for reasoning under uncertainty. In this logic, propositions are labeled with a representation of the arguments which support their validity. Arguments may then be aggregated to collect more information about the potential validity of the propositions of interest. We make the notion of aggregation primitive to the logic, and then define strength mappings from sets of arguments to one of a number of possible dictionaries. This provides a uniform framework which incorporates a number of numerical and symbolic techniques for assigning subjective confidences to propositions on the basis of their supporting arguments. These aggregation techniques are also described with examples.
LEARNING IN RELATIONAL DATABASES: A ROUGH SET APPROACH
Authors: Hu Xiaohua , Cercone Nick
Published: April 2007

Knowledge discovery in databases, or dala mining, is an important direction in the development of data and knowledge‐based systems. Because of the huge amount of data stored in large numbers of existing databases, and because the amount of data generated in electronic forms is growing rapidly, it is necessary to develop efficient methods to extract knowledge from databases. An attribute‐oriented rough set approach has been developed for knowledge discovery in databases. The method integrates machine‐learning paradigm, especially learning‐from‐examples techniques, with rough set techniques. An attribute‐oriented concept tree ascension technique is first applied in generalization, which substantially reduces the computational complexity of database learning processes. Then the cause‐effect relationship among the attributes in the database is analyzed using rough set techniques, and the unimportant or irrelevant attributes are eliminated. Thus concise and strong rules with little or no redundant information can be learned efficiently. Our study shows that attribute‐oriented induction combined with rough set theory provide an efficient and effective mechanism for knowledge discovery in database systems.
INTELLIGENT BEHAVIOR IN MACHINES EMERGING FROM A COLLECTION OF INTERACTIVE CONTROL STRUCTURES
Authors: Cherian Sunil , Troxell Wade
Published: April 2007

Control strategies that decompose the competence of an agent into independent, task‐achieving control structures are emerging as viable alternatives to the notion that a robot is an explicit symbol processing device with input and output extensions in the form of sensors and actuators. This approach draws inspiration from ethology and the cognitive sciences, where the competence of biological creatures is seen to be a result of the successful combination of several distinct behavior patterns that enable them to interact effectively with their environments.

The distinction between classical approaches that view intelligent behavior as the outcome of symbolic manipulations and an alternate approach that asserts that it is the careful integration of distributed, goal‐competent control structures that lead to intelligent behavior is analyzed in detail. It is found that this dichotomy can be said to arise from the paradigm that is chosen to represent the knowledge at the disposal of the agent. Structurally encoded knowledge requiring an active interpreter for the knowledge to be exhibited in action leads to the symbol processing paradigm for intelligent behavior, whereas the interactive model for knowledge representation assumes that the knowledge at the disposal of an active agent resides within goal‐competent, interactive control structures.

A formalism is developed for representing the goal‐directed nature of these interactive control structures with clear control‐module boundaries. An implementation is then presented to demonstrate some of the basic features of this methodology.
A STRATEGIC METAGAME PLAYER FOR GENERAL CHESS‐LIKE GAMES
Authors: Pell Barney
Published: April 2007

This paper introduces METAGAMER, the first program designed within the paradigm of Metagame‐playing (Metagame). This program plays games in the class of symmetric chess‐like games, which includes chess, Chinese chess, checkers, draughts, and Shogi. METAGAMER takes as input the rules of a specific game and analyzes those rules to construct an efficient representation and an evaluation function for that game; they are used by a generic search engine. The strategic analysis performed by METAGAMER relates a set of general knowledge sources to the details of the particular game. Among other properties, this analysis determines the relative value of the different pieces in a given game. Although METAGAMER does not learn from experience, the values resulting from its analysis are qualitatively similar to values used by experts on known games and are sufficient to produce competitive performance the first time METAGAMER plays a new game. Besides being the first Metagame‐playing program, this is the first program to have derived useful piece values directly from analysis of the rules of different games. This paper describes the knowledge implemented in METAGAMER, illustrates the piece values METAGAMER derives for chess and checkers, and discusses experiments with METAGAMER on both existing and newly generated games.
INTERACTIVE SEMANTIC ANALYSIS OF TECHNICAL TEXTS
Authors: Delisle Sylvain , Barker Ken , Copek Terry , Szpakowicz Stan
Published: April 2007

Sentence syntax is the basis for organizing semantic relations in TANKA, a project that aims to acquire knowledge from technical text. Other hallmarks include an absence of precoded domain‐specific knowledge; significant use of public‐domain generic linguistic information sources; involvement of the user as a judge and source of expertise; and learning from the meaning representations produced during processing. These elements shape the realization of the TANKA project: implementing a trainable text processing system to propose correct semantic interpretations to the user. A three‐level model of sentence semantics, including a comprehensive Case system, provides the framework for TANKA's representations. Text is first processed by the DIPETT parser, which can handle a wide variety of unedited sentences. The semantic analysis module HAIKU then semi‐automatically extracts semantic patterns from the parse trees and composes them into domain knowledge representations. HAIKU's dictionaries and main algorithm are described with the aid of examples and traces of user interaction. Encouraging experimental results are described and evaluated.
LOCALIZED TEMPORAL REASONING USING SUBGOALS AND ABSTRACT EVENTS
Authors: Lin Shieu‐Hong , Dean Thomas
Published: April 2007

We are concerned with temporal reasoning problems where there is uncertainty about the order in which events occur. The task of temporal reasoning is to derive an event sequence consistent with a given set of ordering constraints to achieve a goal. Previous research shows that the associated decision problems are hard even for very restricted cases. In this article, we investigate locality in event ordering and causal dependencies. We present a localized temporal reasoning algorithm that uses subgoals and abstract events to exploit locality. The computational efficiency of our algorithm for a problem instance is quantified by the inherent locality in the instance. We theoretically demonstrate the substantial improvement in performance gained by exploiting locality. This work provides solid evidence of the usefulness of localized reasoning in exploiting locality.
COMPUTATION OF BEST BOUNDS OF PROBABILITIES FROM UNCERTAIN DATA
Authors: Luo Chengjie , Lobo Clement Yu, and Jorge , Wang Gaoming , Pham Tracy , Yu Clement
Published: April 2007

An uncertainty reasoning method is presented in this article. The method can be used to compute from a given set of conditional probabilities the best lower bounds and the best upper bounds of those conditional probabilities that are not explicitly provided. The computation of the best upper(lower) bound of such a conditional probability relies on solution of a linear programming problem. Some reduction techniques are proposed in this article to improve the efficiency of our uncertainty reasoning method. As illustrated in Section 4.3, for many uncertainty reasoning problems in medical diagnosis, by using our reduction techniques, the best range of a conditional probability, which is specified by a lower bound and an upper bound, can be computed in polynomial time in terms of the number of basic events involved in the reasoning.
A REFLECTION ON THE EFFECTS OF TRANSPORT COSTS WITHIN THE NEW ECONOMIC GEOGRAPHY
Authors: Alonso‐Villar Olga
Published: April 2007

This paper analyzes, in the light of recent contributions of New Economic Geography models, the spatial consequences of transport cost reductions. So far, the role of transport costs have been only partially unveiled; papers focused either on the Dixit‐Stiglitz‐Iceberg framework or on the alternative framework put forth by Ottaviano et al. (2002),—which departs from the former in preferences and transport modeling. This paper goes a step further, offering a comprehensive view that includes the two approaches, in contexts both of two and of more than two locations. Contrary to other revisions of the literature focused mainly on the centripetal forces included in these models, we emphasize the role of dispersion forces. In a two‐location setting, the results seem quite robust against changes in transportation modeling, so that considering either multiplicative transport costs or additive the predictions are identical. However, when allowing for a multilocation setup, the analysis becomes more complex.
Lexical errors as writing quality predictors*
Authors: Llach María Pilar Agustín
Published: April 2007

Abstract The present paper investigates the role of lexical errors as writing quality predictors and assessment criteria of written compositions. Careful scrutiny of the compositions revealed a hierarchy of lexical error types regarding their order of frequency. The instrument used for assessment was The Profile which evaluates written production in terms of its communicative value. Analysis of the data yielded quite revealing results, since the different types of lexical errors correlated to different degrees with the score given to the composition and its vocabulary score. Considering that the presence of lexical errors does not play any relevant role in the quality of the composition and the assessment of vocabulary use in writing, we can conclude that the correlation found between lexical richness and writing quality does not hold when only errors instead of general richness are regarded. Encouraging students to take risks using partly known words and making creative use of vocabulary is called for in the light of the results of the present research.
Polysemy Across Image Schemas: SwedishFRAM*
Authors: Hellberg Staffan
Published: April 2007

Abstract. There has been some reluctance among scholars to accept the possibility that the image schema structure for a polysemous word can vary from one subsense to another, one image schema dominating for one subsense and another for the other. The aim of this article is to demonstrate that this possibility does indeed exist. For the polysemous Swedish adverb or particlefram, it is shown that no less than four image schemas are primary in different subsenses, viz. thefront‐backschema, thecentre‐peripheryschema, thesource‐path‐goalschema, and thecontainerschema. Furthermore, although these schemas also appear in backgrounded functions in other subsenses, thus securing the network, no single schema is present in all subsenses.
Fordham, feeling, and countertransference: reflections on defences of the self
Authors: Astor James
Published: April 2007

Abstract:  This is a paper about the difficulties we as analysts get into when we find that a patient has activated something in our unconscious which we cannot resolve in our work with them. Fordham described at the end of his life, in a number of papers, his difficulties and discomfort at not being able to resolve an impasse with one of his patients. From the conversations we had about this situation I knew this caused them both a lot of pain. After Fordham's death his former patient consulted me. Arising from these consultations I describe how I have understood the impasse to have arisen between Fordham and his patient. This paper links character and clinical interests, personality and impasse, developmental failures and defences of the self. It is a personal statement in which I have struggled to represent the meaning in the pain these two men suffered during their analytic engagement, which lasted more than ten years. The theme of fathers and sons was central to the problem.