The Experts below are selected from a list of 303 Experts worldwide ranked by ideXlab platform
Thomas Krennwallner - One of the best experts on this subject based on the ideXlab platform.
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ICLP (Technical Communications) - Promoting Modular Nonmonotonic Logic Programs
2020Co-Authors: Thomas KrennwallnerAbstract:Modularity in Logic Programming has gained much attention over the past years. To date, many formalisms have been proposed that feature various aspects of modularity. In this paper, we present our current work on Modular Nonmonotonic Logic Programs (MLPs), which are Logic programs under answer set semantics with modules that have contextualized input provided by other modules. Moreover, they allow for (mutually) recursive module calls. We pinpoint issues that are present in such cyclic module systems and highlight how MLPs addresses them.
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promoting modular Nonmonotonic Logic programs
International Conference on Logic Programming, 2011Co-Authors: Thomas KrennwallnerAbstract:Modularity in Logic Programming has gained much attention over the past years. To date, many formalisms have been proposed that feature various aspects of modularity. In this paper, we present our current work on Modular Nonmonotonic Logic Programs (MLPs), which are Logic programs under answer set semantics with modules that have contextualized input provided by other modules. Moreover, they allow for (mutually) recursive module calls. We pinpoint issues that are present in such cyclic module systems and highlight how MLPs addresses them.
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relevance driven evaluation of modular Nonmonotonic Logic programs
International Conference on Logic Programming, 2009Co-Authors: Minh Daotran, Michael Fink, Thomas Eiter, Thomas KrennwallnerAbstract:Modular Nonmonotonic Logic programs (MLPs) under the answer-set semantics have been recently introduced as an ASP formalism in which modules can receive context-dependent input from other modules, while allowing (mutually) recursive module calls. This can be used for more succinct and natural problem representation at the price of an exponential increase of evaluation time. In this paper, we aim at an efficient top-down evaluation of MLPs, considering only calls to relevant module instances. To this end, we generalize the well-known Splitting Theorem to the MLP setting and present notions of call stratification, for which we determine sufficient conditions. Call-stratified MLPs allow to split module instantiations into two parts, one for computing input of module calls, and one for evaluating the calls themselves with subsequent computations. Based on these results, we develop a top-down evaluation procedure that expands only relevant module instantiations. Finally, we discuss syntactic conditions for its exploitation.
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LPNMR - Relevance-Driven Evaluation of Modular Nonmonotonic Logic Programs
Logic Programming and Nonmonotonic Reasoning, 2009Co-Authors: Minh Dao-tran, Michael Fink, Thomas Eiter, Thomas KrennwallnerAbstract:Modular Nonmonotonic Logic programs (MLPs) under the answer-set semantics have been recently introduced as an ASP formalism in which modules can receive context-dependent input from other modules, while allowing (mutually) recursive module calls. This can be used for more succinct and natural problem representation at the price of an exponential increase of evaluation time. In this paper, we aim at an efficient top-down evaluation of MLPs, considering only calls to relevant module instances. To this end, we generalize the well-known Splitting Theorem to the MLP setting and present notions of call stratification, for which we determine sufficient conditions. Call-stratified MLPs allow to split module instantiations into two parts, one for computing input of module calls, and one for evaluating the calls themselves with subsequent computations. Based on these results, we develop a top-down evaluation procedure that expands only relevant module instantiations. Finally, we discuss syntactic conditions for its exploitation.
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ICLP - Modular Nonmonotonic Logic Programming Revisited
Logic Programming, 2009Co-Authors: Minh Dao-tran, Michael Fink, Thomas Eiter, Thomas KrennwallnerAbstract:Recently, enabling modularity aspects in Answer Set Programming (ASP) has gained increasing interest to ease the composition of program parts to an overall program. In this paper, we focus on modular Nonmonotonic Logic programs (MLP) under the answer set semantics, whose modules may have contextually dependent input provided by other modules. Moreover, (mutually) recursive module calls are allowed. We define a model-theoretic semantics for this extended setting, show that many desired properties of ordinary Logic programming generalize to our modular ASP, and determine the computational complexity of the new formalism. We investigate the relationship of modular programs to disjunctive Logic programs with well-defined input/output interface (DLP-functions) and show that they can be embedded into MLPs.
Thomas Eiter - One of the best experts on this subject based on the ideXlab platform.
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WoMO - Distribution and Modularity in Nonmonotonic Logic Programming.
2020Co-Authors: Thomas EiterAbstract:In the recent years, there has been a trend towards considering computation in a distributed setting, due to the fact that increasingly not only data is linked via media such as the internet, but also computational entities which process and exchange data and knowledge. This leads to the formation of (possibly complex) systems of interlinked entities, based on possibly heterogenous formalisms, posing challenging issues on semantics and computation. The concept of modularity, which in computer science and engineering is a key to structured program development, naturally links to this as a tool for defining semantics of distributed systems, and has been widely studied, e.g., in the area of ontologies. In line with the general development, distribution and modularity have been also been receiving increased attention in Logic programming, at several levels of language expressiveness, from distributed (plain) datalog to advanced Nonmonotonic Logic programming semantics. In this talk, we shall address the issue of distribution and modularity for Logic programming under the answer set semantics, which is one of the most widely used semantics for nonmontonic Logic programs do date and at the heart of the Answer Set Programming paradigm for declarative problem solving. It appeared that the issue of modularity for answer set semantics is nontrivial, due to its Nonmonotonicity. For the same reason, also the issue of efficient distributed evaluation, assuming a reasonable behavior of the semantics for a program composed of distributed modules, is a challenging problem. We shall discuss these issues, pointing out that modularity and distribution admit different solutions for semantics, depending on the underlying view of a system of Logic programs. We then illustrate this view on particular formalisms that have been developed at the Vienna University of Technology in the last years, including modular Nonmonotonic Logic programs (Modular ASP) and Nonmonotonic multi-context systems (MCS). For these formalisms, various semantics have been developed, as well as experimental prototype implementations that take local or distributed evaluation into account, adopting different realization schemes. While considerable progress has been achieved, further work is needed to arrive at highly efficient solvers.
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distribution and modularity in Nonmonotonic Logic programming
WoMO, 2012Co-Authors: Thomas EiterAbstract:In the recent years, there has been a trend towards considering computation in a distributed setting, due to the fact that increasingly not only data is linked via media such as the internet, but also computational entities which process and exchange data and knowledge. This leads to the formation of (possibly complex) systems of interlinked entities, based on possibly heterogenous formalisms, posing challenging issues on semantics and computation. The concept of modularity, which in computer science and engineering is a key to structured program development, naturally links to this as a tool for defining semantics of distributed systems, and has been widely studied, e.g., in the area of ontologies. In line with the general development, distribution and modularity have been also been receiving increased attention in Logic programming, at several levels of language expressiveness, from distributed (plain) datalog to advanced Nonmonotonic Logic programming semantics. In this talk, we shall address the issue of distribution and modularity for Logic programming under the answer set semantics, which is one of the most widely used semantics for nonmontonic Logic programs do date and at the heart of the Answer Set Programming paradigm for declarative problem solving. It appeared that the issue of modularity for answer set semantics is nontrivial, due to its Nonmonotonicity. For the same reason, also the issue of efficient distributed evaluation, assuming a reasonable behavior of the semantics for a program composed of distributed modules, is a challenging problem. We shall discuss these issues, pointing out that modularity and distribution admit different solutions for semantics, depending on the underlying view of a system of Logic programs. We then illustrate this view on particular formalisms that have been developed at the Vienna University of Technology in the last years, including modular Nonmonotonic Logic programs (Modular ASP) and Nonmonotonic multi-context systems (MCS). For these formalisms, various semantics have been developed, as well as experimental prototype implementations that take local or distributed evaluation into account, adopting different realization schemes. While considerable progress has been achieved, further work is needed to arrive at highly efficient solvers.
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relevance driven evaluation of modular Nonmonotonic Logic programs
International Conference on Logic Programming, 2009Co-Authors: Minh Daotran, Michael Fink, Thomas Eiter, Thomas KrennwallnerAbstract:Modular Nonmonotonic Logic programs (MLPs) under the answer-set semantics have been recently introduced as an ASP formalism in which modules can receive context-dependent input from other modules, while allowing (mutually) recursive module calls. This can be used for more succinct and natural problem representation at the price of an exponential increase of evaluation time. In this paper, we aim at an efficient top-down evaluation of MLPs, considering only calls to relevant module instances. To this end, we generalize the well-known Splitting Theorem to the MLP setting and present notions of call stratification, for which we determine sufficient conditions. Call-stratified MLPs allow to split module instantiations into two parts, one for computing input of module calls, and one for evaluating the calls themselves with subsequent computations. Based on these results, we develop a top-down evaluation procedure that expands only relevant module instantiations. Finally, we discuss syntactic conditions for its exploitation.
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LPNMR - Relevance-Driven Evaluation of Modular Nonmonotonic Logic Programs
Logic Programming and Nonmonotonic Reasoning, 2009Co-Authors: Minh Dao-tran, Michael Fink, Thomas Eiter, Thomas KrennwallnerAbstract:Modular Nonmonotonic Logic programs (MLPs) under the answer-set semantics have been recently introduced as an ASP formalism in which modules can receive context-dependent input from other modules, while allowing (mutually) recursive module calls. This can be used for more succinct and natural problem representation at the price of an exponential increase of evaluation time. In this paper, we aim at an efficient top-down evaluation of MLPs, considering only calls to relevant module instances. To this end, we generalize the well-known Splitting Theorem to the MLP setting and present notions of call stratification, for which we determine sufficient conditions. Call-stratified MLPs allow to split module instantiations into two parts, one for computing input of module calls, and one for evaluating the calls themselves with subsequent computations. Based on these results, we develop a top-down evaluation procedure that expands only relevant module instantiations. Finally, we discuss syntactic conditions for its exploitation.
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ICLP - Modular Nonmonotonic Logic Programming Revisited
Logic Programming, 2009Co-Authors: Minh Dao-tran, Michael Fink, Thomas Eiter, Thomas KrennwallnerAbstract:Recently, enabling modularity aspects in Answer Set Programming (ASP) has gained increasing interest to ease the composition of program parts to an overall program. In this paper, we focus on modular Nonmonotonic Logic programs (MLP) under the answer set semantics, whose modules may have contextually dependent input provided by other modules. Moreover, (mutually) recursive module calls are allowed. We define a model-theoretic semantics for this extended setting, show that many desired properties of ordinary Logic programming generalize to our modular ASP, and determine the computational complexity of the new formalism. We investigate the relationship of modular programs to disjunctive Logic programs with well-defined input/output interface (DLP-functions) and show that they can be embedded into MLPs.
Chiaki Sakama - One of the best experts on this subject based on the ideXlab platform.
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Inductive equivalence in clausal Logic and Nonmonotonic Logic programming
Machine Learning, 2011Co-Authors: Chiaki Sakama, Katsumi InoueAbstract:This paper provides a Logical framework for comparing inductive capabilities among agents having different background theories. A background theory is called inductively equivalent to another background theory if the two theories induce the same hypotheses for any observation. Conditions of inductive equivalence change depending on the Logic of representation languages and the Logic of induction or inductive Logic programming (ILP). In this paper, we consider clausal Logic and Nonmonotonic Logic programs as representation languages for background theories. Then we investigate conditions of inductive equivalence in four different frameworks of induction, cautious induction , brave induction , learning from satisfiability , and descriptive induction . We observe that several induction algorithms in Horn ILP systems require weaker conditions of equivalence under restricted problem settings. We address that inductive equivalence can be used for verification and evaluation of induction algorithms, and argue problems for optimizing background theories in ILP.
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inductive equivalence in clausal Logic and Nonmonotonic Logic programming
Machine Learning, 2011Co-Authors: Chiaki Sakama, Katsumi InoueAbstract:This paper provides a Logical framework for comparing inductive capabilities among agents having different background theories. A background theory is called inductively equivalent to another background theory if the two theories induce the same hypotheses for any observation. Conditions of inductive equivalence change depending on the Logic of representation languages and the Logic of induction or inductive Logic programming (ILP). In this paper, we consider clausal Logic and Nonmonotonic Logic programs as representation languages for background theories. Then we investigate conditions of inductive equivalence in four different frameworks of induction, cautious induction , brave induction , learning from satisfiability , and descriptive induction . We observe that several induction algorithms in Horn ILP systems require weaker conditions of equivalence under restricted problem settings. We address that inductive equivalence can be used for verification and evaluation of induction algorithms, and argue problems for optimizing background theories in ILP.
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Brave induction: a Logical framework for learning from incomplete information
Machine Learning, 2009Co-Authors: Chiaki Sakama, Katsumi InoueAbstract:This paper introduces a novel Logical framework for concept-learning called brave induction . Brave induction uses brave inference for induction and is useful for learning from incomplete information. Brave induction is weaker than explanatory induction which is normally used in inductive Logic programming , and is stronger than learning from satisfiability , a general setting of concept-learning in clausal Logic. We first investigate formal properties of brave induction, then develop an algorithm for computing hypotheses in full clausal theories. Next we extend the framework to induction in Nonmonotonic Logic programs . We analyze computational complexity of decision problems for induction on propositional theories. Further, we provide examples of problem solving by brave induction in systems biology, requirement engineering, and multiagent negotiation.
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combining answer sets of Nonmonotonic Logic programs
Lecture Notes in Computer Science, 2006Co-Authors: Chiaki Sakama, Katsumi InoueAbstract:This paper studies compositional semantics of Nonmonotonic Logic programs. We suppose the answer set semantics of extended disjunctive programs and consider the following problem. Given two programs P 1 and P 2 , which have the sets of answer sets AS(P 1 ) and AS(P 2 ), respectively; find a program Q which has answer sets as minimal sets S∪T for S from AS(P 1 ) and T from AS(P 2 ). The program Q combines answer sets of P 1 and P 2 , and provides a compositional semantics of two programs. Such program composition has application to coordinating knowledge bases in multi-agent environments. We provide methods for computing program composition and discuss their properties.
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CLIMA - Combining answer sets of Nonmonotonic Logic programs
Lecture Notes in Computer Science, 2005Co-Authors: Chiaki Sakama, Katsumi InoueAbstract:This paper studies compositional semantics of Nonmonotonic Logic programs. We suppose the answer set semantics of extended disjunctive programs and consider the following problem. Given two programs P1 and P2, which have the sets of answer sets AS(P1) and AS(P2), respectively; find a program Q which has answer sets as minimal sets S∪ T for S from AS(P1) and T from AS(P2). The program Q combines answer sets of P1 and P2, and provides a compositional semantics of two programs. Such program composition has application to coordinating knowledge bases in multi-agent environments. We provide methods for computing program composition and discuss their properties.
D. Pedreschi - One of the best experts on this subject based on the ideXlab platform.
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Nondeterministic, Nonmonotonic Logic databases
IEEE Transactions on Knowledge and Data Engineering, 2001Co-Authors: F. Giannotti, G. Manco, M. Nanni, D. PedreschiAbstract:We consider an extension of Datalog with mechanisms for temporal, Nonmonotonic, and nondeterministic reasoning, which we refer to as Datalog++. We show, by means of examples, its flexibility in expressing queries concerning aggregates and data cube. Also, we show how iterated fixpoint and stable model semantics can be combined to the purpose of clarifying the semantics of Datalog++ programs and supporting their efficient execution. Finally, we provide a more concrete implementation strategy on which basis the design of optimization techniques tailored for Datalog++ is addressed.
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query answering in nondeterministic Nonmonotonic Logic databases
Flexible Query Answering Systems, 1998Co-Authors: F. Giannotti, G. Manco, M. Nanni, D. PedreschiAbstract:We consider in this paper an extension of Datalog with mechanisms for temporal, non monotonic and non deterministic reasoning, which we refer to as Datalog++. We show, by means of examples, its flexibility in expressing queries of increasing difficulty, up to aggregates and data cube. Also, we show how iterated fixpoint and stable model semantics can be combined to the purpose of clarifying the semantics of Datalog++ programs, and supporting their efficient execution. On this basis, the design of appropriate optimization techniques for Datalog++ is also briefly discussed.
J.j.-p. Tsai - One of the best experts on this subject based on the ideXlab platform.
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A Logic-based transformation system
IEEE Transactions on Knowledge and Data Engineering, 1998Co-Authors: J.j.-p. Tsai, Bing Li, T. WeigertAbstract:In spite of advances in various transformation systems the transformation of a Nonmonotonic-Logic-based requirements specification into a procedural (imperative) language program has not been investigated. This paper presents a Logic-based transformation system that can transform a Nonmonotonic-Logic-based specification, the Frame-and-Rule Oriented Requirement Specification Language (FRORL), into procedural language programs. We discuss how to handle Nonmonotonic inheritance in FRORL and then establish a matrix-based data flow and dependency analysis mechanism to find all the possible data transformation paths in a Logic-based specification. Using a newly developed algorithm, we can adjust the execution sequence of a Logic-based specification so that the functions included in the Logic-based specification can be represented by a sequential procedural language program.
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A computationally tractable Nonmonotonic Logic
IEEE Transactions on Knowledge and Data Engineering, 1994Co-Authors: T.j. Weigert, J.j.-p. TsaiAbstract:Nonmonotonic Logic is intended to apply specifically to situations where the initial information is incomplete. Using Nonmonotonic reasoning procedures we shall be able to jump to conclusions, but withdraw them later when we gain additional information. A number of Nonmonotonic Logics have been introduced and widely discussed. Nonmonotonic Logics tend to be introduced proof theoretically, and little attention is paid to their semantic characteristics or their computational tractability. We address both of these issues by presenting a Nonmonotonic Logic for the Herbrand subset of first-order predicate Logic. This Nonmonotonic Logic is shown to be both sound and complete. Theories formulated in this Logic can be executed in Logic programming fashion.
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A framework of a Logic-based transformation system
[1992] Proceedings. The Sixteenth Annual International Computer Software and Applications Conference, 1992Co-Authors: J.j.-p. Tsai, R.-y. Sheu, Bing LiAbstract:The authors present a framework for a transformation system which can transform a Nonmonotonic Logic-based specification language, FRORL, into various kinds of procedural language programs. They discuss how to handle Nonmonotonic inheritance in FRORL. A matrix-based data flow and dependency analysis mechanism is established to find all the possible data transformation paths in a Logic-based specification. An algorithm is proposed to adjust the execution sequence of a Logic-based specification so that the functions included in the Logic-based specification can be represented by a procedural language program.
