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13
Managed multicontext systems
 In International Joint Conference on Artificial Intelligence (IJCAI
, 2011
"... Multicontext systems (MCS) are a powerful framework for interlinking heterogeneous knowledge sources. They model the flow of information among different reasoning components (called contexts) in a declarative way, using socalled bridge rules, where contexts and bridge rules may be nonmonotonic. We ..."
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Cited by 11 (2 self)
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Multicontext systems (MCS) are a powerful framework for interlinking heterogeneous knowledge sources. They model the flow of information among different reasoning components (called contexts) in a declarative way, using socalled bridge rules, where contexts and bridge rules may be nonmonotonic. We considerably generalize MCS to managed MCS (mMCS): while the original bridge rules can only add information to contexts, our generalization allows arbitrary operations on context knowledge bases to be freely defined, e.g., deletion or revision operators. The paper motivates and introduces the generalized framework and presents several interesting instances. Furthermore, we consider inconsistency management in mMCS and complexity issues. 1
Evolving multicontext systems
, 2014
"... Abstract. Managed MultiContext Systems (mMCSs) provide a general framework for integrating knowledge represented in heterogeneous KR formalisms. However, mMCSs are essentially static as they were not designed to run in a dynamic scenario. In this paper, we introduce evolving MultiContext Systems ..."
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Abstract. Managed MultiContext Systems (mMCSs) provide a general framework for integrating knowledge represented in heterogeneous KR formalisms. However, mMCSs are essentially static as they were not designed to run in a dynamic scenario. In this paper, we introduce evolving MultiContext Systems (eMCSs), a general and flexible framework which inherits from mMCSs the ability to integrate knowledge represented in heterogeneous KR formalisms, and at the same time is able to both react to, and reason in the presence of commonly temporary dynamic observations, and evolve by incorporating new knowledge. We show that eMCSs are indeed very general and expressive enough to capture several existing KR approaches that model dynamics of knowledge. 1
Exploiting Unfounded Sets for HEXProgram Evaluation
 13TH EUROPEAN CONFERENCE ON LOGICS IN ARTIFICIAL INTELLIGENCE (JELIA 2012), SEPTEMBER 2628, 2012
"... HEX programs extend logic programs with external computations through external atoms, whose answer sets are the minimal models of the FaberLeonePfeiferreduct. As already reasoning from Horn programs with nonmonotonic external atoms of polynomial complexity is on the second level of the polynomi ..."
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Cited by 5 (5 self)
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HEX programs extend logic programs with external computations through external atoms, whose answer sets are the minimal models of the FaberLeonePfeiferreduct. As already reasoning from Horn programs with nonmonotonic external atoms of polynomial complexity is on the second level of the polynomial hierarchy, answer set checking needs special attention; simply computing reducts and searching for smaller models does not scale well. We thus extend an approach based on unfounded sets to HEX and integrate it in a Conflict Driven Clause Learning framework for HEX program evaluation. It reduces the check to a search for unfounded sets, which is more efficiently implemented as a SAT problem. We give a basic encoding for HEX and show optimizations by additional clauses. Experiments show that the new approach significantly decreases runtime.
Solving modular model expansion tasks
 In Proceedings of the 25th International Workshop on Logic Programming (WLP’11), volume abs/1109.0583. Computing Research Repository (CoRR
, 2011
"... Abstract. The work we describe here is a part of a research program of developing foundations of declarative solving of search problems. We consider the model expansion task as the task representing the essence of search problems where we are given an instance of a problem and are searching for a so ..."
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Abstract. The work we describe here is a part of a research program of developing foundations of declarative solving of search problems. We consider the model expansion task as the task representing the essence of search problems where we are given an instance of a problem and are searching for a solution satisfying certain properties. Such tasks are common in artificial intelligence, formal verification, computational biology. Recently, the model expansion framework was extended to deal with multiple modules. In the current paper, inspired by practical combined solvers, we introduce an algorithm to solve model expansion tasks for modular systems. We show that our algorithm closely corresponds to what is done in practice in different areas such as Satisfiability Modulo Theories (SMT), Integer Linear
Evolving bridge rules in evolving multicontext systems
, 2014
"... In open environments, agents need to reason with knowledge from various sources, represented in different languages. Managed MultiContext Systems (mMCSs) allow for the integration of knowledge from different heterogeneous sources in an effective and modular way, where socalled bridge rules expres ..."
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Cited by 3 (3 self)
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In open environments, agents need to reason with knowledge from various sources, represented in different languages. Managed MultiContext Systems (mMCSs) allow for the integration of knowledge from different heterogeneous sources in an effective and modular way, where socalled bridge rules express how information flows between the contexts. The problem is that mMCSs are essentially static as they were not designed to run in a dynamic scenario. Some recent approaches, among them evolving MultiContext Systems (eMCSs), extend mMCSs by allowing not only the ability to integrate knowledge represented in heterogeneous KR formalisms, but at the same time to both react to, and reason in the presence of commonly temporary dynamic observations, and evolve by incorporating new knowledge. These approaches, however, only consider the dynamics of the knowledge bases, whereas the dynamics of the bridge rules, i.e., the dynamics of how the information flows, is neglected. In this paper, we fill this gap by building upon the framework of eMCSs by further extending it with the ability to update the bridge rules of each context taking into account an incoming stream of observed bridge rules. We show that several desirable properties are satisfied in our framework, and that the important problem of consistency management can be dealt with in our framework.
Eliminating Unfounded Set Checking for HEXPrograms
, 2012
"... HEXprograms are an extension of the Answer Set Programming (ASP) paradigm incorporating external means of computation into the declarative programming language through socalled external atoms. Their semantics is defined in terms of minimal models of the FaberLeonePfeifer (FLP) reduct. Developi ..."
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HEXprograms are an extension of the Answer Set Programming (ASP) paradigm incorporating external means of computation into the declarative programming language through socalled external atoms. Their semantics is defined in terms of minimal models of the FaberLeonePfeifer (FLP) reduct. Developing native solvers for HEXprograms based on an appropriate notion of unfounded sets has been subject to recent research for reasons of efficiency. Although this has lead to an improvement over naive minimality checking using the FLP reduct, testing for foundedness remains a computationally expensive task. In this work we improve on HEXprogram evaluation in this respect by identifying a syntactic class of programs, that can be efficiently recognized and allows to entirely skip the foundedness check. Moreover, we develop criteria for decomposing a program into components, such that the search for unfounded sets can be restricted. Observing that our results apply to many HEXprogram applications provides analytic evidence for the significance and effectiveness of our approach, which is complemented by a brief discussion of preliminary experimental validation.
On Efficient Evolving MultiContext Systems
"... Abstract. Managed MultiContext Systems (mMCSs) provide a general framework for integrating knowledge represented in heterogeneous KR formalisms. Recently, evolving MultiContext Systems (eMCSs) have been introduced as an extension of mMCSs that add the ability to both react to, and reason in the p ..."
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Abstract. Managed MultiContext Systems (mMCSs) provide a general framework for integrating knowledge represented in heterogeneous KR formalisms. Recently, evolving MultiContext Systems (eMCSs) have been introduced as an extension of mMCSs that add the ability to both react to, and reason in the presence of commonly temporary dynamic observations, and evolve by incorporating new knowledge. However, the general complexity of such an expressive formalism may simply be too high in cases where huge amounts of information have to be processed within a limited short amount of time, or even instantaneously. In this paper, we investigate under which conditions eMCSs may scale in such situations and we show that such polynomial eMCSs can be applied in a practical use case. 1
Towards Efficient Evolving MultiContext Systems (Preliminary Report)
"... Abstract. Managed MultiContext Systems (mMCSs) provide a general framework for integrating knowledge represented in heterogeneous KR formalisms. Recently, evolving MultiContext Systems (eMCSs) have been introduced as an extension of mMCSs that add the ability to both react to, and reason in the p ..."
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Cited by 1 (1 self)
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Abstract. Managed MultiContext Systems (mMCSs) provide a general framework for integrating knowledge represented in heterogeneous KR formalisms. Recently, evolving MultiContext Systems (eMCSs) have been introduced as an extension of mMCSs that add the ability to both react to, and reason in the presence of commonly temporary dynamic observations, and evolve by incorporating new knowledge. However, the general complexity of such an expressive formalism may simply be too high in cases where huge amounts of information have to be processed within a limited short amount of time, or even instantaneously. In this paper, we investigate under which conditions eMCSs may scale in such situations and we show that such polynomial eMCSs can be applied in a practical use case. 1
Advancing MultiContext Systems by Inconsistency Management ⋆
, 1107
"... Abstract. MultiContext Systems are an expressive formalism to model (possibly) nonmonotonic information exchange between heterogeneous knowledge bases. Such information exchange, however, often comeswith unforseen sideeffects leading to violation of constraints, making the system inconsistent, an ..."
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Abstract. MultiContext Systems are an expressive formalism to model (possibly) nonmonotonic information exchange between heterogeneous knowledge bases. Such information exchange, however, often comeswith unforseen sideeffects leading to violation of constraints, making the system inconsistent, and thus unusable. Although there are many approaches to assess and repair a single inconsistent knowledge base, the heterogeneous nature of MultiContext Systems poses problems which have not yet been addressed in a satisfying way: How to identify and explain a inconsistency that spreads over multiple knowledge bases with different logical formalisms (e.g., logic programs and ontologies)? What are the causes of inconsistency if inference/information exchange is nonmonotonic (e.g., absent information as cause)? How to deal with inconsistency if access to knowledge bases is restricted (e.g., companies exchange information, but do not allow arbitrary modifications to their knowledge bases)? Many traditional approaches solely aim for a consistent system, but automatic removal of inconsistency is not always desireable. Therefore a human operator has to be supported in finding the erroneous parts contributing to the inconsistency. In my thesis those issues will be adressed mainly from a foundational perspective, while our research project also provides algorithms and prototype implementations. 1
Symmetry Breaking for Answer Set Programming
, 2010
"... In the context of answer set programming, this work investigates symmetry detection and symmetry breaking to eliminate symmetric parts of the search space and, thereby, simplify the solution process. We contribute a reduction of symmetry detection to a graph automorphism problem which allows to extr ..."
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In the context of answer set programming, this work investigates symmetry detection and symmetry breaking to eliminate symmetric parts of the search space and, thereby, simplify the solution process. We contribute a reduction of symmetry detection to a graph automorphism problem which allows to extract symmetries of a logic program from the symmetries of the constructed coloured graph. The correctness of our reduction is rigorously proven. We also propose an encoding of symmetrybreaking constraints in terms of permutation cycles and use only generators in this process which implicitly represent symmetries and always with exponential compression. These ideas are formulated as preprocessing and implemented in a completely automated flow that first detects symmetries from a given answer set program, adds symmetrybreaking constraints, and can be applied to any existing answer set solver. We demonstrate computational impact on benchmarks versus direct application of the solver. Furthermore, we explore symmetry breaking for answer set programming in two domains: first, constraint answer set programming as a novel approach to represent and solve constraint satisfaction problems, and second, distributed nonmonotonic multicontext systems.