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  • Blackwell Publishing Ltd  (416)
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  • 1
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    Oxford, UK : Blackwell Publishing Ltd
    Computational intelligence 9 (1993), S. 0 
    ISSN: 1467-8640
    Source: Blackwell Publishing Journal Backfiles 1879-2005
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    Computational intelligence 9 (1993), S. 0 
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    Computational intelligence 9 (1993), S. 0 
    ISSN: 1467-8640
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    Notes: Glasgow's revival of the “imagery debate” in computational terms provides a renewed opportunity to review the role of logical reasoning in general problem solving. Of special interest is the long-standing distinction between analogical or depictive problem representations, and the more abstract linguistic forms typified by traditional formal logic syntax.In our brief statement, we recall that logical reasoning rests on semantics not syntax, and that the concepts of soundness, completeness, and consistency are manifest in both depictive and linguistic representations. We emerge with two conclusions: (1) enduring confusion regarding computational aspects of the “imagery debate” arise from long-standing confusion regarding key logical concepts, and related notions such as epistemological versus heuristic adequacy, logical versus probabilistic independence, and direct versus indirect representations; (2) the desire for depictive reasoning methods is ultimately motivated by human needs, not computational needs.
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    Notes: Whilst I agree largely with Janice Glasgow's position paper, there are a number of relevant subtle and important issues that she does not address, concerning the variety of forms and techniques of representation available to intelligent agents, and issues concerned with different levels of description of the same agent, where that agent includes different virtual machines at different levels of abstraction. I shall also suggest ways of improving on her array-based representation by using a general network representation, though I do not know whether efficient implementations are possible.
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    Computational intelligence 9 (1993), S. 0 
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    Notes: The basic algorithms involved in reason maintenance in the standard ATMS is known to have a computational complexity that is exponential in the worst case. Yet, also in average-case problem solving, the ATMS often lays claim to a major part of the computational effort spent by a problem solver/ATMS system. In this paper, we argue that within the limits of the worst-case computational complexity, it is possible to improve on the average-case complexity of reason maintenance and query processing by eliminating computation that is of no relevance to the problem solver's performance. To this purpose, we present a set of algorithms designed to control the effort spent by the ATMS on label updating. The basic idea underlying these algorithms is that of lazy evaluation: labels are not automatically maintained on all datums but are computed only when needed (either directly or indirectly) by the problem solver. The algorithms have been implemented in the LazyRMS with which we have experimented in the context of model-based diagnosis; our experiments show a substantial saving in the computational effort spent on reason maintenance.
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  • 29
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    Computational intelligence 9 (1993), S. 0 
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    Notes: We define an argument system to be a pair consisting of a set of inference rules and a set of completeness conditions. Inference rules are used to build arguments. Completeness conditions are used to define argument structures, which are sets of arguments supporting belief sets. We reformulate Reiter's default logic as special argument systems. This enables us, among other things, to apply the negation-as-failure rule to general default theories. We also speculate on some other potential uses of our argument systems.
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  • 30
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    Computational intelligence 9 (1993), S. 0 
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    Notes: Search is fundamental to artificial intelligence (AI) and numerous sophisticated search methods have been developed. We present a general, simple model of search processes and use it to analytically determine some typical behavior when applied to large problems. In particular, this identifies abrupt changes in overall search cost as small improvements are made in the underlying method. We also examine the robustness of this model's predictions in a range of more realistic cases. More generally, we introduce a criterion for determining when average case results reflect typical behavior which allows the method developed here to be used for investigating other large-scale behaviors of complex AI systems.
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    Computational intelligence 9 (1993), S. 0 
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    Notes: This paper describes an original approach to semantics representation based on the use of a non-strict functional programming language with polymorphic typing. This approach provides a unified formalism needing no preprocessing or postprocessing to the functional language itself: parsing and semantics are declared naturally using function definition and evaluation is done by lambda application along the lines of Montague. We show that by changing only the model we can, after parsing, compute either the truth value of a sentence or its parse tree.
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    Computational intelligence 9 (1993), S. 0 
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    Topics: Computer Science
    Notes: Recognizing the plan underlying a query aids in the generation of an appropriate response. In this paper, we address the problem of how to generate cooperative responses when the user's plan is ambiguous. We show that it is not always necessary to resolve the ambiguity, and provide a procedure that estimates whether the ambiguity matters to the task of formulating a response. The procedure makes use of the critiquing of possible plans and identifies plans with the same fault. We illustrate the process of critiquing with examples. If the ambiguity does matter, we propose to resolve the ambiguity by entering into a clarification dialogue with the user and provide a procedure that performs this task. Together, these procedures allow a question-answering system to take advantage of the interactive and collaborative nature of dialogue in order to recognize plans and resolve ambiguity. This work therefore presents a view of generation in advice-giving contexts which is different from the straightforward model of a passive selection of responses to questions asked by users. We also report on a trial implementation in a course-advising domain, which provides insights on the practicality of the procedures and directions for future research.
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  • 33
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    Computational intelligence 9 (1993), S. 0 
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    Notes: 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.
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  • 34
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    Computational intelligence 9 (1993), S. 0 
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    Notes: Bayesian networks provide a natural, concise knowledge representation method for building knowledge-based systems under uncertainty. We consider domains representable by general but sparse networks and characterized by incremental evidence where the probabilistic knowledge can be captured once and used for multiple cases. Current Bayesian net representations do not consider structure in the domain and lump all variables into a homogeneous network. In practice, one often directs attention to only part of the network within a period of time; i.e., there is “localization” of queries and evidence. In such case, propagating evidence through a homogeneous network is inefficient since the entire network has to be updated each time. This paper derives reasonable constraints, which can often be easily satisfied, that enable a natural {localization preserving) partition of a domain and its representation by separate Bayesian subnets. The subnets are transformed into a set of permanent junction trees such that evidential reasoning takes place at only one of them at a time; and marginal probabilities obtained are identical to those that would be obtained from the homogeneous network. We show how to swap in a new junction tree, and absorb previously acquired evidence. Although the overall system can be large, computational requirements are governed by the size of one junction tree.
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    Computational intelligence 9 (1993), S. 0 
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    Notes: We investigate the problem of learning two-layer neural nets of nonoverlapping perceptrons where each input unit is connected to one and only one hidden unit. We first show that this restricted problem with no overlap at all between the receptive fields of the hidden units is as hard as the general problem (with total overlap) if the learner uses examples only. However, if membership queries are allowed, the restricted problem is indeed easier to solve. We give a learning algorithm that uses examples and membership queries to PAC learn the intersection of K-nonoverlapping perceptrons, regardless of whether the instance space in Boolean, discrete, or continuous. An extension of this algorithm is proven to PAC learn two-layer nets with K-nonoverlapping perceptrons. The simulations performed indicate that both algorithms are fast and efficient.
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    Notes: 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.
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    Computational intelligence 9 (1993), S. 0 
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    Notes: 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.
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    Notes: Inheritance reasoners have traditionally been viewed as argument systems, or algorithms that determine reasonable conclusions by constructing acceptable arguments. While the intended meaning of links in such networks is understood, formal semantic accounts are troublesome, as are semantic accounts of the inference process. We adopt a different perspective, suggesting that links be interpreted as conditional sentences with appropriate truth conditions rather than uninterpreted “reasons.” The conditional logic CT4D is used for this purpose. Furthermore, we characterize inference in our networks in terms of preferred (or minimal) models. In the process, we identify some key differences between our account of inference and those based on the notion of inferential distance, specifically with respect to the stability of reasoning. Key words: nonmonotonic reasoning, inheritance hierarchies, minimal models, conditional logic.
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    Computational intelligence 9 (1993), S. 0 
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    Notes: This paper focuses on the semantics of Telos, a language for representing knowledge about information systems. Telos is intended to support the development of information systems, especially in the requirements modeling phase. An object-oriented representational framework is supported by Telos. Its features include aggregation, generalization, and classification, the treatment of attributes as first-class objects and the explicit representation of time. Telos also provides an assertion sublanguage for expressing deductive rules and integrity constraints. A possible-worlds semantics is defined for Telos knowledge bases. This semantics is intended to capture the peculiarities involved in the interpretation of temporal expressions. The integration of time has also inspired the treatment of existence in Telos. An ontology of objects based on the property of existence is proposed. In the spirit of KRYPTON, Telos knowledge bases are specified functionally, in terms of the operations provided for querying and updating them. This knowledge-level analysis will allow us to specify exactly what a knowledge base can be ASK-ed or TELL-ed about the domain of discourse. Soundness, consistency, and completeness results have also been proven to complete the specification of Telos knowledge bases. This formal account of the language provides a logical framework that can be used to verify the correctness of any proposed implementation of the system.
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    Computational intelligence 8 (1992), S. 0 
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    Computational intelligence 8 (1992), S. 0 
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    Notes: 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.
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    Computational intelligence 8 (1992), S. 0 
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    Notes: 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.
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    Computational intelligence 8 (1992), S. 0 
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    Notes: Generating action sequences to achieve a set of goals is a computationally difficult task. When multiple goals are present, the problem is even worse. Although many solutions to this problem have been discussed in the literature, practical solutions focus on the use of restricted mechanisms for planning or the application of domain dependent heuristics for providing rapid solutions (i.e., domain-dependent planning). One previously proposed technique for handling multiple goals efficiently is to design a planner or even a set of planners (usually domain-dependent) that can be used to generate separate plans for each goal. The outputs are typically either restricted to be independent and then concatenated into a single global plan, or else they are merged together using complex heuristic techniques. In this paper we explore a set of limitations, less restrictive than the assumption of independence, that still allow for the efficient merging of separate plans using straightforward algorithmic techniques.In particular, we demonstrate that for cases where separate plans can be individually generated, we can define a set of limitations on the allowable interactions between goals that allow efficient plan merging to occur. We propose a set of restrictions that are satisfied across a significant class of planning domains. We present algorithms that are efficient for special cases of multiple plan merging, propose a heuristic search algorithm that performs well in a more general case (where alternative partially ordered plans have been generated for each goal), and describe an empirical study that demonstrates the efficiency of this search algorithm.
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    Computational intelligence 8 (1992), S. 0 
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    Notes: Based on psychological studies which show that metaphors and other non-literal constructions are comprehended in the same amount of time as comparable literal constructions, some researchers have concluded that literal meaning is not computed during comprehension of non-literal constructions. In this paper, we suggest that the empirical evidence does not rule out the possibility that literal meaning is constructed. We present a computational model of comprehension of non-literal expressions which is consistent with the data, but in which literal meaning is computed. This model has been implemented as part of a unification-based natural language processing system, called LINK.
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    Notes: There are two pertinent themes in the study of idioms in the area of natural language processing. Firstly, idioms should be defined and located in the space of non-literal expressions. This will be the first aim of this paper. Secondly, a processing model should be developed. In this paper, the application of knowledge representation techniques in three different models for the representation and processing of idioms are discussed. The first, a symbolic procedural model extends the two-level model which was originally developed in computational morphology. The second is a simple localist connectionist model. The third, a symbolic hierarchical model, represents idioms as part of a lexicon conceived as an inheritance hierarchy. A comparison between the models is made in which the focus lies on the resolution of the ambiguity of idioms, the relation between the literal and non-literal interpretation and the syntactic flexibility of idiomatic expressions.
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    Notes: Metallel is a program that incorporates marker passing techniques within a preference/collative semantics framework. This allows for the simultaneous generation of literal and non-literal meaning representations, while allowing for a much greater degree of parallelism during processing. In addition, we have integrated metonymic and metaphoric inferencing into one procedure, arguing that at least some types of metaphor can be represented as parallel metonymies. A number of examples are presented which show that metallel's output is roughly equivalent to conventional, rule-based approaches to metonymy.
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    Notes: Once viewed as a rhetorical and superficial language phenomenon, metaphor is now recognized to serve a fundamental role in our conceptual structuring and language comprehension processes. In particular, it is argued that certain experiential metaphors based upon intuitions of spatial relations are inherent in the conceptual organization of our most abstract thoughts. In this paper we present a two-stage computational model of metaphor interpretation which employs a spatially founded semantics to broadly characterize the meaning carried by a metaphor in terms of a conceptual scaffolding, an interim meaning structure around which a fuller interpretation is fleshed out over time. We then present a semantics for the construction of conceptual scaffolding which is based upon core metaphors of collocation, containment and orientation. The goal of this scaffolding is to maintain the intended association of ideas even in contexts in which system knowledge is insufficient for a complete interpretation. This two-stage system of scaffolding and elaboration also models the common time lapse between initial metaphor comprehension and full metaphor appreciation. Several mechanisms for deriving elaborative inference from scaffolding structures, particularly in cases of novel or creative metaphor, are also presented. While the system developed in this paper has significant practical application, it also demonstrates that core spatial metaphors clearly play a central role in metaphor comprehension.
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    Notes: 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.
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    Notes: Evidence from real discourse suggests that beliefs and other mental states (propositional attitudes) are often viewed by speakers and other agents in a metaphorical way. Typical metaphors are MIND-AS-CONTAINER—the view of the mind as a container, with thoughts being physical objects inside it—or IDEAS-AS-INTERNAL-UTTERANCES—the view of thoughts as natural language utterances inside an agent's head. It is therefore necessary for AI systems for mental-state representation/reasoning to reason within such views. This approach contrasts with the highly abstract logical stance adopted in most propositional attitude research. A formal representation scheme based on the various metaphors has been partially developed. In this paper, it is mainly the MIND-AS-CONTAINER segment of the formal representation scheme that is detailed. Inference processes operating over the scheme are also presented. The crucial distinguishing feature of the representation scheme is that the description of mental states is directly based on physical predicates, objects and so on, as opposed to abstract, tailor-made, mental ones. That is, the representation scheme is itself explicitly metaphor-imbued.
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    Notes: 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.
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    Notes: A linguistic form's compositional, timeless meaning can be surrounded or even contradicted by various social, aesthetic, or analogistic companion meanings. This paper addresses a series of problems in the structure of spoken language discourse, including turn-taking and grounding. It views these processes as composed of fine-grained actions, which resemble speech acts both in resulting from a computational mechanism of planning and in having a rich relationship to the specific linguistic features which serve to indicate their presence. The resulting notion of Conversation Acts is more general than speech act theory, encompassing not only the traditional speech acts but turn-taking, grounding, and higher-level argumentation acts as well. Furthermore, the traditional speech acts in this scheme become fully joint actions, whose successful performance requires full listener participation. This paper presents a detailed analysis of spoken language dialogue. It shows the role of each class of conversation acts in discourse structure, and discusses how each class can be processed and recognized. Conversation acts, it will be seen, better account for the success of conversation than speech act theory alone. They also provide a pragmatic view of meaning in which the literal/non-literal distinction is simply irrelevant.
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    Notes: 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.
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    Notes: The paper by Sacks and Doyle that is the focus of this debate resembles previous papers by Cheeseman and McDermott, leaping from the observation that a specific application of some AI technology is unable to solve a problem to the conclusion that the technology itself is of limited value. We argue that claims such as this should be made more cautiously in the future, and make constructive suggestions about future qualitative physics research based on Sacks and Doyle's results.
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    Notes: 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.
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    Notes: 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.
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    Notes: The economic theory of rationality promises to equal mathematical logic in its importance for the mechanization of reasoning. We survey the growing literature on how the basic notions of probability, utility, and rational choice, coupled with practical limitations on information and resources, influence the design and analysis of reasoning and representation systems.
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    Notes: A formal description is given of a connectionist implementation of discrete relaxation for labelled graph matching. The network is shown to converge. The desired behavior of the algorithm is formally specified; then it is proved that the result of the relaxation meets the formal goal. The network is limited by complexity considerations to the detection and propagation of unary and binary consistency constraints. The application is fast parallel indexing into a memory of object models, based on a visually derived junction/link structure description. Implementation experiments are presented, and explicit and exact space and time requirements are developed.
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    Notes: A truth maintenance system is a subsystem that manages the utilization of assumptions in the reasoning process of a problem solver. Doyle's original motivation for creating a truth maintenance system was to augment a reasoning system with a control strategy for activities concerning its nonmonotonic state of beliefs. Hitherto, much effort has been invested in designing and implementing the concept of truth maintenance, and little effort has been dedicated to the formalization that is essential to understanding it. This paper provides a complete formalization of the principle of truth maintenance. Motivated by Reiter and de Kleer's preliminary report on the same subject, this paper extends their study and gives a formal account of the concept of truth maintenance under the general title of assumption-based reasoning. The concept of assumption-based theory is defined, and the notions of explanation and direct consequence are presented as forms of plausible conclusions with respect to this theory. Additionally, the concepts of extension and irrefutable sentences are discussed together with other variations of explanation and direct consequence. A set of algorithms for computing these conclusions for a given theory are presented using the notion of prime implicates. Finally, an extended example on Boolean circuit diagnosis is shown to exemplify these ideas.
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    Notes: Much research in machine learning has been focused on the problem of symbol-level learning (SLL), or learning to improve the performance of a program given examples of its behavior on typical inputs. A common approach to symbol-level learning is to use some sort of mechanism for saving and later reusing the solution paths used to solve previous search problems. Examples of such mechanisms are macro-operator learning, explanation-based learning, and chunking. However, experimental evidence that these mechanisms actually improve performance is inconclusive. This paper presents a formal framework for analysis of symbol-level learning programs, and then uses this framework to investigate a series of solution-path caching mechanisms which provably improve performance. The analysis of these mechanisms is illuminating in many respects; in particular, in order to obtain positive results, it is necessary to use a novel representation for a set of solution paths, and also to apply certain unusual optimizations to a set of solution paths. Several of the predictions made by the model have been confirmed by recently published experiments.
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    Notes: Consider the construction of an expert system by encoding the knowledge of different experts. Suppose the knowledge provided by each expert is encoded into a knowledge base. Then the process of combining the knowledge of these different experts is an important and nontrivial problem. We study this problem here when the expert systems are considered to be first-order theories. We present techniques for resolving inconsistencies in such knowledge bases. We also provide algorithms for implementing these techniques.
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    Notes: This article proposes a framework in which knowledge compilation can be exploited in a principled manner for the task of generating natural language. We have constructed an utterance generator for one side of a realistic dialogue that exploits compiled knowledge of, for instance, the effects of discourse pragmatics on text plans, and the effects of register, style, and politeness on text realization. The motivation for this work is the significant impact that compiled knowledge has on the speed of language generation.
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    Notes: In this paper, I present an architecture for generating extended text. This architecture is implemented in a system, Salix, which incrementally generates natural language texts whose structure is derived from the domain structure of the subject matter. The architecture is composed of data-driven, domain-independent strategies for producing increments of text. The strategies include metastrategies that combine or choose among all strategies that are applicable at each increment or decide what to do if no strategy applies. Salix's capabilities are demonstrated in generating texts, in the domains of houses and families, that are comparable to descriptions elicited from human speakers. Salix has also been utilized to generate texts about text style (Germain 1991). The approach to text generation presented here is compared to others in the literature along the dimensions of local organization, coherence, focusing, and domain independence. An argument is made for the approach presented here that locally organizes and incrementally generates coherent text.
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    Notes: 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.
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    Notes: Looking to the future, generators will have more knowledge of language and will have to deal with inputs that are very rich in information. As a result, several problems will become more acute, including selecting what to say at the subproposition level and dealing with interaction among goals and dependencies among choices. This paper explains how these problems arise and why they are hard to handle within traditional architectures for generation. It also discusses why these issues have not been well addressed, including the current lack of demanding applications, excessive emphasis on linguistic traditions, the use of reverse engineering to determine generator inputs, and the tendency to research only one issue at a time.
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  • 90
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    Oxford, UK : Blackwell Publishing Ltd
    Computational intelligence 7 (1991), S. 0 
    ISSN: 1467-8640
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Notes: 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.
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  • 91
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    Oxford, UK : Blackwell Publishing Ltd
    Computational intelligence 7 (1991), S. 0 
    ISSN: 1467-8640
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Notes: This paper notes some structural features of naturally occurring, extended explanations and argues that current generation methodologies are inadequate for determining high-level structure. We then present a computational model for generating high-level structure, which is based on the hypothesis that high-level structure is distinct from text structure at lower levels and is determined by the material to be conveyed rather than by independent, recursive text structuring devices. We propose that high-level structure can be determined by bottom-up processes that attempt to satisfy speaker, listener, and compositional goals, after which top-down strategies can be used to organize the material about the selected framework.Cet article relève certaines caractéristiques structurales ?explications étendues à occurrence naturelle et soutient que les méthodes de génération courantes ne permettent pas de déterminer adéquatement une stratégie de haut niveau. Les auteurs présentent ensuite un modèle computationnel de géneration de structures de haut niveau qui est basé sur ľhypothèse qu'une structure de haut niveau est différente ?une structure de texte aux nivaux inféiieurs, et qu'elle est déterminée par les données qui doivent ětre transmises plutǒt que par des mécanismes indépendants et récursifs de structure de texte. lis soutiennent qu'une structure de haut niveau peut ětre déterminée àľaide ?'un processus ascendant qui essaie de rencontrer les objectifs du locuteur, de ľauditeur et de composition, et que des stratégies descendantes peuvent ensuite ětre utilisées pour organiser les données a propos du cadre choisi.
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  • 92
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    Oxford, UK : Blackwell Publishing Ltd
    Computational intelligence 7 (1991), S. 0 
    ISSN: 1467-8640
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
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  • 93
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    Oxford, UK : Blackwell Publishing Ltd
    Computational intelligence 7 (1991), S. 0 
    ISSN: 1467-8640
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
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  • 94
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    Oxford, UK : Blackwell Publishing Ltd
    Computational intelligence 7 (1991), S. 0 
    ISSN: 1467-8640
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
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  • 95
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    Oxford, UK : Blackwell Publishing Ltd
    Computational intelligence 10 (1994), S. 0 
    ISSN: 1467-8640
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
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  • 96
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    Oxford, UK : Blackwell Publishing Ltd
    Computational intelligence 10 (1994), S. 0 
    ISSN: 1467-8640
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Notes: In many head-final languages such as German, Hindi, Japanese, and Korean, but also in some other languages such as Russian, arguments of a verb can occur in any order. Furthermore, arguments can occur outside of their clause (“long-distance scrambling”). Long-distance scrambling presents a challenge both to linguistic theory and to formal frameworks for linguistic description because it is very unconstrained: in a given sentence, there is no bound on the number of elements that can be scrambled nor on the distance over which each element can scramble. We discuss two formal frameworks related to tree-adjoining grammar. First, we show how scrambling facts from Korean can be handled by nonlocal multicomponent TAG (MC-TAG). Then, we argue that overt vWt-movement in German makes this analysis unattractive, and suggest a new version of MC-TAG, called V-TAG, which can handle both Korean and German word order variation. Interestingly, this new version has more attractive computational properties than nonlocal MC-TAG. We conclude that this formalism is an attractive basis for the development of psycholinguistic processing models and practical parsers alike.
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  • 97
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    Oxford, UK : Blackwell Publishing Ltd
    Computational intelligence 10 (1994), S. 0 
    ISSN: 1467-8640
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Notes: A number of grammatical formalisms have been proposed to describe the syntax of natural languages, and the universal recognition problems for some of those classes of grammars have been studied. A universal recognition problem for a class Q of grammars is the one to decide, taking a grammar G ∈ G and a string ui as an input, whether G can generate w or not. In this paper, the computational complexities of the universal recognition problems for parallel multiple context-free grammars, multiple context-free grammars, and their subclasses are discussed.
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  • 98
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    Oxford, UK : Blackwell Publishing Ltd
    Computational intelligence 10 (1994), S. 0 
    ISSN: 1467-8640
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Notes: We show how multicomponent TAGs, although in their “local” version equivalent to “simple” TAGs, enable one to associate the derived structures with a richer set of derivations. This is especially useful for representing some nonlocal dependencies such as wh-extraction out of NP or extraposition, as soon as one interprets the derivation structures as representing the predicate-argument dependencies. However, there is a formal alternative in the formalism of synchronous TAGs that achieves a similar result, namely, that associates standard syntactic derivations with nonisomorphic semantic derivations, and relies on the latter to represent the dependency relations. We show that the latter treatment accounts for a different range of extraposition facts in French, where the relationship between the head noun and its extraposed dependent is a semantic one.Nous montrons comment les TAGs ensemblistes “locales” (MCTAGs), qui sont équivalentes aux TAGs simples, permettent ?associer aux structures syntaxiques dérivées un ensemble plus large de structures dérivationnelles. Cela est particulièrement utile pour la représentation des dépendances non locales qu'on observe dans les extractions hors du groupe nominal et les extrapositions, à partirdu moment oùľon interprète les arbres de dérivation comme représentant les relations de dépendance. II existe toutefois une autre possibilityé dans le cadre des TAGs synchrones qui associe aux dérivations syntaxiques standard des dérivations sémantiques non isomorphes et interprète les relations de dépendance en se basant sur ces dernières. Nous montrons que cette deuxième possibilityé est mieux adaptée pour des cas ?extraposition en français où la relation de dépendance entre le nom těte et ľélément extraposé est ?ordre sémantique.
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  • 99
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    Oxford, UK : Blackwell Publishing Ltd
    Computational intelligence 10 (1994), S. 0 
    ISSN: 1467-8640
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Notes: This paper extends the “parsing as deduction” approach to tree-adjoining grammars by showing how a TAG recognition problem can be reduced to a Datalog deduction problem, and presents an SLD selection rule that makes the proof search correspond to a top-down parse using the original grammar. Just as in the DCG extension of context-free grammars, this approach permits nodes to be labeled with firsl-order terms (rather than only atomic symbols). Finally the paper discusses implementation matters, and describes how the control rule can be efficiently implemented in Prolog.
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  • 100
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    Oxford, UK : Blackwell Publishing Ltd
    Computational intelligence 10 (1994), S. 0 
    ISSN: 1467-8640
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Notes: It is possible within tree-adjoining grammar to reproduce many of the syntactic analyses originally formulated by linguists in transformational terms. To the extent that these analyses are well motivated empirically, this fact makes TAG interesting for use in developing computational learning and processing models (Joshi 1990; Frank 1992; Rambow 1994), since the use of other nontransformational formalisms sometimes forces choices of linguistic description different from those ordinarily made by descriptive syntacticians. Thus, using TAG, one can take advantage in the construction of parsers and learners of the computational tractability of a mathematically restrictive formalism without having to reinvent empirical syntax in order to do so. At the same time, TAG analyses are not identical in every detail to their transformational counterparts; and it is interesting to compare them where they diverge. The differences arise because of a fundamental difference in the way that syntactic recursion is treated in the two frameworks. In TAG, recursive structures are generated by composing elementary syntactic objects, with the result that recursion is factored apart from the representation of local syntactic dependencies. By contrast, in transformational grammar, as in many other frameworks, recursive structure and local dependencies are represented together in a single, full representation of a complex sentence. Because of this difference in the treatment of recursion, it often turns out, when TAG is used to emulate a transformational analysis, that the TAG version has advantages, of both elegance and empirical coverage, over the original. This paper is a demonstration in a new empirical domain, that of nominal constructions, of the advantages of TAG-based syntax. By presenting a linguistically detailed account of these constructions and showing the advantages of using TAG to analyze them, we strengthen the case for the use of mathematically constrained and computationally tractable representational systems in competence-based as well as in computational linguistics.
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