The HORNE Reasoning System. Revision

Allen, James F.; Giuliano, Mark; Frisch, Alan M.

doi:10.21236/ada221796

Cited by 5 publications

(4 citation statements)

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“…The logic programming language HORNE (Allen & Miller, 1986) has a reasonably well developed sort (or type) mechanism. Four declarations are available for specifying knowledge of the sort hierarchy.…”

Section: Many-sorted Logic Programmingmentioning

confidence: 99%

“…The logic programming language HORNE (Allen & Miller, 1986) we mentioned above also includes a structured type facility, called REP, which we describe now. A role is a unary function defined on a particular sort.…”

Section: Integrating Objects With Typesmentioning

confidence: 99%

“…However, in the absence of a formal semantics for the latter one cannot be certain whether the two are equivalent. For example, multiple inheritance is possible in LOGIN, but it is not clear from the HORNE manual (Allen & Miller, 1986) whether it is also possible in REP. Also, it is possible to specify in LOGIN that certain compositions of selectors always denote the same value, but there does not appear to be a corresponding facility in REP.…”

Section: Integrating Objects With Typesmentioning

confidence: 99%

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Taxonomic reasoning with many-sorted logics

Cohn

1989

Artif Intell Rev

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This paper provides an introduction to many-sorted logics and motivates their use for representation and reasoning. Perhaps the most important reason to be interested in many-sorted logic is that computational efficiency can be achieved because the search space can be smaller and the length of a derivation shorter than in unsorted logic. There are many possible many-sorted logics of varying degrees of expressiveness, and the dimensions in which many-sorted logics differ are outlined and logics at various points in this space described. The relationship of manysorted logic to unsorted logic is discussed and the reason why many-sorted logics derivations may be shorter is. demonstrated. The paper concludes with a discussion of some many-sorted logic programming languages and some implementation issues. I n t r o d u c t i o nLogic has been associated with AI since its earliest days: for example McCarthy's Advice Taker project (McCarthy, 1968) was formulated using logic as a knowledge representation language. Moreover, logic has a wide following among AI practitioners and researchers today as a glance at the proceedings of almost any AI conference will confirm. There are several ways in which logic and AI relate. Logic may be used directly as a representation language (e.g. Green, 1969; Michalski, 1983;Hayes, 1985), as an implementation language for AI tools and systems through the use of a logic programming language (e.g. Bundy et al., 1979;Bratko, 1986), logic may be applied as tool to analyse the semantics of formerly ad hoc representation systems (e.g. Hayes, 1979) or as a formalism in which to build a rational reconstruction of an existing but poorly understood AI program (e.g. Bundy, 1983b).Of course logic has also received much criticism from within the AI community over the years and continues to do so (for example see the debate started by McDermott (1987) in Vol. 3(3) of the journal Computational Intelligence). This is not the place to further this debate; however, two criticisms that have been often repeated are of importance to the present context: logic as a knowledge representation language has been criticized for being 'flat' and 'unstructured' (e.g. Minsky, 89

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Section: Many-sorted Logic Programmingmentioning

confidence: 99%

Section: Integrating Objects With Typesmentioning

confidence: 99%

Section: Integrating Objects With Typesmentioning

confidence: 99%

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Taxonomic reasoning with many-sorted logics

Cohn

1989

Artif Intell Rev

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“…The HORNE Reasoning System [Allen et al, 1983], a lisp-embedded typed horn clause theorem prover, is used as the starting point for our knowledge retrieval mechanism. The incorporation of the discourse mechanism is under development.…”

Section: Example: Dialoguementioning

confidence: 99%

A plan recognition model for subdialogues in conversations

1987

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Previous· plan-based approaches to analyzing task-oriented dialogues have not been able to account for many phenomena of concern to discourse analysts. We have developed a model based on a hierarchy of plans and meta-plans that accounts for such interrupting subdialogues as clarifications and corrections, while maintaining the advantages of the plan-based approach. Previous plan-based approaches to analyzing task-oriented dialogues have not been able to account for many phenomena of concern to discourse analysts. We have developed a model based on a hierarchy of plans and meta-plans that accounts for such interrupting subdialogues as clarifications and corrections, while maintaining the advantages of the plan-based approach.

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Parsing with restricted quantification: an initial demonstration1

Frisch

1986

Computational Intelligence

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The primary goal of this paper is to illustrate how smaller deductive search spaces can be obtained by extending a logical language with restricted quantification and tailoring an inference system to this extension. The illustration examines the search spaces for a bottom-up parse of a sentence with a series of four strongly equivalent grammars. The grammars are stated in logical languages of increasing expressiveness, each restatement resulting in a more concise grammar and a smaller search space.A secondary goal is to point out an area where further research could yield results useful to the design of efficient parsers, particularly for grammatical formalisms that rely heavily on feature systems.L'objectif principal de cet article est de montrer comment on peut obtenir de plus petits espaces de recherche deductive en ttendant un langage logique avec une quantification restreinte et en adaptant un systkme d'inference a cette extension. On examine les espaces de recherche Crees par un analyse ascendante d'une phrase faite a I'aide de quatre grammaires fortement tquivalentes. Chacune des grammaires est dtfinie avec un langage logique plus expressif que celui de la grammaire prkddente. Chaque redefinition permet d'obtenir une grammaire plus concise et un espace de recherche plus restreint.Un des objectifs secondaires de cet article est de pointer les endroits oB des recherches permettraient d'obtenir des resultats utiles pour la conception d'analyseurs efficaces, plus particulierement pour des formalismes grammaticaux qui reposent principalement sur des systhes de traits.Mots clh: analyse, quantification restreinte, logique avec esptxes, grammaires logiques, deduction automatique, traitement automatique du langage naturel, linguistique informatique, raisonnement automatist, strategic de recherche B implication minimale, systemes de traits, unification avec esj&ces, report de contraintes.

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The HORNE Reasoning System. Revision

Cited by 5 publications

References 0 publications

Taxonomic reasoning with many-sorted logics

Taxonomic reasoning with many-sorted logics

A plan recognition model for subdialogues in conversations

Parsing with restricted quantification: an initial demonstration1

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