29 found
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  1.  5
    Joohyung Lee & Vladimir Lifschitz, Safe Formulas in the General Theory of Stable Models (Preliminary Report).
    Safe first-order formulas generalize the concept of a safe rule, which plays an important role in the design of answer set solvers. We show that any safe sentence is equivalent, in a certain sense, to the result of its grounding—to the variable-free sentence obtained from it by replacing all quantifiers with multiple conjunctions and disjunctions. It follows that a safe sentence and the result of its grounding have the same stable models, and that stable models of a safe sentence can (...)
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  2.  9
    Vladimir Lifschitz (2015). The Dramatic True Story of the Frame Default. Journal of Philosophical Logic 44 (2):163-176.
    This is an expository article about the solution to the frame problem proposed in 1980 by Raymond Reiter. For years, his “frame default” remained untested and suspect. But developments in some seemingly unrelated areas of computer science—logic programming and satisfiability solvers—eventually exonerated the frame default and turned it into a basis for important applications.
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  3.  56
    Vladimir Lifschitz, What is Answer Set Programming?
    Answer set programming (ASP) is a form of declarative programming oriented towards difficult search problems. As an outgrowth of research on the use of nonmonotonic reasoning in knowledge representation, it is particularly useful in knowledge-intensive applications. ASP programs consist of rules that look like Prolog rules, but the computational mechanisms used in ASP are different: they are based on the ideas that have led to the creation of fast satisfiability solvers for propositional logic.
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  4.  5
    Vladimir Lifschitz & Fangkai Yang (2013). Functional Completion. Journal of Applied Non-Classical Logics 23 (1-2):121-130.
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  5.  1
    Vladimir Lifschitz (2001). On Calculational Proofs. Annals of Pure and Applied Logic 113 (1-3):207-224.
    This note is about the “calculational style” of presenting proofs introduced by Dijkstra and Scholten and adopted in some books on theoretical computer science. We define the concept of a calculation, which is a formal counterpart of the idea of a calculational proof. The definition is in terms of a new formalization DS of predicate logic. Any proof tree in the system DS can be represented as a sequence of calculations. This fact shows that any logically valid predicate formula has (...)
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  6.  11
    Vladimir Lifschitz, L. Morgenstern & D. Plaisted, Knowledge Representation and Classical Logic.
    in Handbook of Knowledge representation, Elsevier, 2008.
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  7.  1
    Vladimir Lifschitz, Why the Monkey Needs the Box: A Serious Look at a Toy Domain.
    “Toy worlds” involving actions, such as the Blocks World and the Monkey and Bananas domain, are often used by researchers in the areas of commonsense reasoning and planning to illustrate and test their ideas. Many of the axioms found in descriptions of these toy worlds are expressions of generalpurpose knowledge, though they are often cast in a form only useful for solving one specific problem and are not faithful representations of general facts that can be used in other domains. Instead (...)
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  8.  6
    Vladimir Lifschitz, Safe Formulas in the General Theory of Stable Models (Preliminary Report).
    Safe first-order formulas generalize the concept of a safe rule, which plays an important role in the design of answer set solvers. We show that any safe sentence is equivalent, in a certain sense, to the result of its grounding—to the variable-free sentence obtained from it by replacing all quantifiers with multiple conjunctions and disjunctions. It follows that a safe sentence and the result of its grounding have the same stable models, and that stable models of a safe sentence can (...)
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  9.  7
    Vladimir Lifschitz, Twelve Definitions of a Stable Model.
    This is a review of some of the definitions of the concept of a stable model that have been proposed in the literature. These definitions are equivalent to each other, at least when applied to traditional Prologstyle programs, but there are reasons why each of them is valuable and interesting. A new characterization of stable models can suggest an alternative picture of the intuitive meaning of logic programs; or it can lead to new algorithms for generating stable models; or it (...)
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  10.  6
    Vladimir Lifschitz (1982). Constructive Assertions in an Extension of Classical Mathematics. Journal of Symbolic Logic 47 (2):359-387.
  11.  5
    Vladimir Lifschitz, Papers Published Between 1996 and 2000.
    (Click here for selected papers published before 1996, and here for papers published after 2000.) V. Lifschitz, Foundations of logic programming ," in Principles of Knowledge Representation , CSLI Publications, 1996, pp. 69-127. E. Giunchiglia, N. Kartha and V. Lifschitz, Representing action: indeterminacy and ramifications ," Artificial Intelligence , Vol. 95, 1997, pp. 409-443. V. Lifschitz, On the logic of causal explanation ," Artificial Intelligence , Vol. 96, 1997, pp. 451-465. V. Lifschitz, Two components of an action language ," Annals (...)
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  12.  1
    Vladimir Lifschitz (1987). Review: Alan Bundy, The Computer Modelling of Mathematical Reasoning. [REVIEW] Journal of Symbolic Logic 52 (2):555-557.
  13.  4
    Joohyung Lee, Vladimir Lifschitz & Hudson Turner, Nonmonotonic Causal Theories.
    cuted actions. It has been applied to several challenge problems in the theory of commonsense knowledge. We study the relationship between this formalism and other work on nonmonotonic reasoning and knowl-.
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  14.  1
    Joohyung Lee & Vladimir Lifschitz, A Knowledge Module: Buying and Selling.
    This note shows how to formalize a small set of general facts about buying and selling. We begin with summarizing properties of buying/selling informally in English, and give examples of consequences of these assumptions. Then we formalize our assumptions in action language C+ with additive fluents and actions and test the adequacy of the proposed formalization using the Causal Calculator.
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  15.  1
    Vladimir Lifschitz, Irrelevant Actions in Plan Generation.
    be irrelevant for achieving the given goal. We make this idea precise by defining, for an action description in language C+, when a subset of its..
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  16.  4
    Vladimir Lifschitz & W. Ren, The Semantics of Variables in Action Descriptions.
    structures, or interpretations, in the sense of first-order logic. In C+, on the other hand, a state is an interpreta-.
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  17.  3
    Vladimir Lifschitz, Almost Definite Causal Theories.
    The language of nonmonotonic causal theories, defined by Norman McCain and Hudson Turner, is an important formalism for representing properties of actions. For causal theories of a special kind, called definite, a simple translation into the language of logic programs under the answer set semantics is available. In this paper we define a similar translation for causal theories of a more general form, called al-.
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  18.  4
    Vladimir Lifschitz, A Reductive Semantics for Counting and Choice in Answer Set Programming.
    In a recent paper, Ferraris, Lee and Lifschitz conjectured that the concept of a stable model of a first-order formula can be used to treat some answer set programming expressions as abbreviations. We follow up on that suggestion and introduce an answer set programming language that defines the mean- ing of counting and choice by reducing these constructs to first-order formulas. For the new language, the concept of a safe program is defined, and its semantic role is investigated. We compare (...)
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  19.  1
    Vladimir Lifschitz, Mathematical Foundations of Answer Set Programming.
    applied, for instance, to developing a decision support system for the Space Shuttle INogueira et al., 2001] and to graph-theoretic problems arising in..
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  20.  2
    Vladimir Lifschitz, Temporal Phylogenetic Networks and Logic Programming.
    The concept of a temporal phylogenetic network is a mathematical model of evolution of a family of natural languages. It takes into account the fact that languages can trade their characteristics with each other when linguistic communities are in contact, and also that a contact is only possible when the languages are spoken at the same time. We show how computational methods of answer set programming and constraint logic programming can be used to generate plausible conjectures about contacts between prehistoric (...)
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  21.  3
    Vladimir Lifschitz, Definitions in Answer Set Programming.
    affects the collection of answer sets. In particular, it is useful to be able to describe the effects of adding definitions to a program with nested expressions, in view of the relation of this class of programs to the input language of the answer set programming system sMonELs. In this..
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  22.  3
    Vladimir Lifschitz, A Modular Action Description Language.
    “Toy worlds” involving actions, such as the blocks world and the Missionaries and Cannibals puzzle, are often used by researchers in the areas of commonsense reasoning and planning to illustrate and test their ideas. We would like to create a database of generalpurpose knowledge about actions that encodes common features of many action domains of this kind, in the same way as abstract algebra and topology represent common features of specific number systems. This paper is a report on the first (...)
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  23.  2
    Vladimir Lifschitz, Actions as Special Cases.
    This paper is motivated by the idea of interaction between two directions of research in knowledge representation: the design of action description languages and the development of libraries of reusable, general-purpose knowledge components. Writing an action description that characterizes actions in terms of their effects, as common today, can be compared to writing a program that does not use standard subroutines. We conjecture that a library of standard descriptions for a number of “basic” actions can facilitate writing, understanding and modifying (...)
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  24.  2
    Vladimir Lifschitz, Selected Papers Published Before 1996.
    (Click here for the papers published between 1996 and 2000, and here for more recent papers.) V. Lifschitz, On the semantics of STRIPS ," in: Reasoning about Actions and Plans , 1987, pp. 1-9. M. Gelfond and V. Lifschitz, The stable model semantics for logic programming ," in Logic Programming: Proceedings of the Fifth International Conference and Symposium , 1988, pp. 1070-1080.
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  25.  2
    Vladimir Lifschitz, Variables in Action Descriptions: Merging C+ with ADL.
    Action description language C+ is more expressive than ADL in many ways; for instance, it addresses the ramification problem. On the other hand, ADL is based on first-order logic, while C+ is only propositional; expressions with variables, which are frequently used when action domains are described in C+, are merely..
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  26. Bart Demoen & Vladimir Lifschitz (2004). Logic Programming 20th International Conference, Iclp 2004, Saint-Malo, France, September 6-10, 2004 : Proceedings.
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  27.  0
    Michael Gelfond, Vladimir Lifschitz, Robert A. Kowalski, Kenneth A. Bowen, Kit Fine & Jens Erik Fenstad (1992). The Stable Model Semantics for Logic Programming. Journal of Symbolic Logic 57 (1):274-277.
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  28. Vladimir Lifschitz & Ilkka Niemelä (2004). Logic Programming and Nonmonotonic Reasoning 7th International Conference, Lpnmr 2004, Fort Lauderdale, Fla., January 6-8, 2004 : Proceedings. [REVIEW]
     
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  29.  0
    S. Iu Maslov, Michael Gelfond & Vladimir Lifschitz (1987). Theory of Deductive Systems and its Applications. Monograph Collection (Matt - Pseudo).
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