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Abduction in Logic Programming
"... Abduction in Logic Programming started in the late 80s, early 90s, in an attempt to extend logic programming into a framework suitable for a variety of problems in Artificial Intelligence and other areas of Computer Science. This paper aims to chart out the main developments of the field over th ..."
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Cited by 612 (76 self)
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Abduction in Logic Programming started in the late 80s, early 90s, in an attempt to extend logic programming into a framework suitable for a variety of problems in Artificial Intelligence and other areas of Computer Science. This paper aims to chart out the main developments of the field over the last ten years and to take a critical view of these developments from several perspectives: logical, epistemological, computational and suitability to application. The paper attempts to expose some of the challenges and prospects for the further development of the field.
ACLP: Abductive Constraint Logic Programming
, 2000
"... This paper presents the framework of Abductive Constraint Logic Programming (ACLP), which integrates Abductive Logic Programming (ALP) and Constraint Logic Programming (CLP). In ACLP, the task of abduction is supported and enhanced by its nontrivial integration with constraint solving. This int ..."
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Cited by 55 (5 self)
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This paper presents the framework of Abductive Constraint Logic Programming (ACLP), which integrates Abductive Logic Programming (ALP) and Constraint Logic Programming (CLP). In ACLP, the task of abduction is supported and enhanced by its nontrivial integration with constraint solving. This integration of constraint solving into abductive reasoning facilitates a general form of constructive abduction and enables the application of abduction to computationally demanding problems
The Wellfounded Semantics Is the Principle of Inductive Definition
 Logics in Arti Intelligence
, 1998
"... . Existing formalisations of (transfinite) inductive definitions in constructive mathematics are reviewed and strong correspondences with LP under least model and perfect model semantics become apparent. I point to fundamental restrictions of these existing formalisations and argue that the wellfou ..."
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Cited by 50 (32 self)
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. Existing formalisations of (transfinite) inductive definitions in constructive mathematics are reviewed and strong correspondences with LP under least model and perfect model semantics become apparent. I point to fundamental restrictions of these existing formalisations and argue that the wellfounded semantics (wfs) overcomes these problems and hence, provides a superior formalisation of the principle of inductive definition. The contribution of this study for LP is that it (re )introduces the knowledge theoretic interpretation of LP as a logic for representing definitional knowledge. I point to fundamental differences between this knowledge theoretic interpretation of LP and the more commonly known interpretations of LP as default theories or autoepistemic theories. The relevance is that differences in knowledge theoretic interpretation have strong impact on knowledge representation methodology and on extensions of the LP formalism, for example for representing uncertainty. Keywo...
ASystem: Problem Solving through Abduction
, 2001
"... System, performing abductive reasoning within the framework of Abductive Logic Programming. It is based on a hybrid computational model that implements the abductive search in terms of two tightly coupled processes: a reduction process of the highlevel logical representation to a lowerlevel co ..."
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Cited by 49 (11 self)
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System, performing abductive reasoning within the framework of Abductive Logic Programming. It is based on a hybrid computational model that implements the abductive search in terms of two tightly coupled processes: a reduction process of the highlevel logical representation to a lowerlevel constraint store and a lowerlevel constraint solving process. A set of initial "proof of principle" experiments demonstrate the versatility of the approach stemming from its declarative representation of problems and the good underlying computational behaviour of the system. The approach offers a general methodology of declarative problem solving in AI where an incremental and modular refinement of the highlevel representation with extra domain knowledge can improve and scale the computational performance of the framework.
The CIFF Proof Procedure for Abductive Logic Programming with Constraints
 In Proceedings JELIA04
, 2004
"... We introduce a new proof procedure for abductive logic programming and present two soundness results. Our procedure extends that of Fung and Kowalski by integrating abductive reasoning with constraint solving and by relaxing the restrictions on allowed inputs for which the procedure can operate ..."
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Cited by 41 (20 self)
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We introduce a new proof procedure for abductive logic programming and present two soundness results. Our procedure extends that of Fung and Kowalski by integrating abductive reasoning with constraint solving and by relaxing the restrictions on allowed inputs for which the procedure can operate correctly. An implementation of our proof procedure is available and has been applied successfully in the context of multiagent systems.
Specification and verification of agent interaction using social integrity constraints
 In LCMAS’03: Logic and Communication in MultiAgent Systems. ENTCS
, 2004
"... In this paper we propose a logicbased social approach to the specification and verification of agent interaction. We firstly introduce integrity constraints about social acts (called Social Integrity Constraints) as a formalism to express interaction protocols and to give a social semantics to the ..."
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Cited by 35 (14 self)
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In this paper we propose a logicbased social approach to the specification and verification of agent interaction. We firstly introduce integrity constraints about social acts (called Social Integrity Constraints) as a formalism to express interaction protocols and to give a social semantics to the behavior of agents, focusing on communicative acts. Then, we discuss several possible kinds of verification of agent interaction, and we show how social integrity constraints can be used to verify some properties in this respect. We focus our attention on static verification of compliance of agent specifications to interaction protocols, and on runtime verification, based on agents ’ observable behavior. We adopt as a running example the NetBill security transaction protocol for the selling and delivery of information goods. 1
From logic programming to multiagent systems
 Annals of Mathematics and AI
, 1999
"... In this paper we present an extension of logic programming (LP) that is suitable not only for the "rational " component of a single agent but also for the "reactive " component and which can encompass multiagent systems. The extension to multiagent systems, in p ..."
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Cited by 34 (9 self)
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In this paper we present an extension of logic programming (LP) that is suitable not only for the &quot;rational &quot; component of a single agent but also for the &quot;reactive &quot; component and which can encompass multiagent systems. The extension to multiagent systems, in particular, arguably brings to LP the main benefits of objectorientation, including encapsulation. We modify an earlier abductive proof procedure and embed it within an agent cycle. The proof procedure incorporates abduction, definitions and integrity constraints within a dynamic environment, where changes can be observed as inputs. The definitions allow rational planning behaviour and the integrity constraints allow reactive, conditionaction type behaviour. The agent cycle provides a resourcebounded mechanism that allows the agent's thinking to be interrupted for the agent to record and assimilate observations as input and execute actions as output, before resuming further thinking. We argue that these extensions of LP, accommodating multitheories embedded in a shared environment, provide the necessary multiagent functionality. We argue that our work extends Shoham's agent0 and the BDI architecture.
Abduction with Negation as Failure for Active and Reactive Rules
 In Proc. AI*IA1999
, 2000
"... . Recent work has suggested abductive logic programming as a suitable formalism to represent active databases and intelligent agents. In particular, abducibles in abductive logic programs can be used to represent actions, and integrity constaints in abductive logic programs can be used to repres ..."
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Cited by 29 (11 self)
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. Recent work has suggested abductive logic programming as a suitable formalism to represent active databases and intelligent agents. In particular, abducibles in abductive logic programs can be used to represent actions, and integrity constaints in abductive logic programs can be used to represent active rules of the kind encountered in active databases and reactive rules incorporating reactive behaviour in agents. One would expect that, in this approach, abductive proof procedures could provide the engine underlying active database management systems and the behaviour of agents. We analyse existing abductive proof procedures and argue that they are inadequate in handling these applications. The inadequacy is due to the inappropriate treatment of negative literals in integrity constraints. We propose a new abductive proof procedure and give examples of how this proof procedure can be used to achieve active behaviour in (deductive) databases and reactivity in agents. Final...
Executing Suspended Logic Programs
 FUNDAMENTA INFORMATICAE
, 1998
"... We present an extension of Logic Programming (LP) which, in addition to ordinary LP clauses, also includes integrity constraints, explicit representation of disjunction in the bodies of clauses and in goals, and suspension of atoms as in concurrent logic languages. The resulting framework aims to ..."
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Cited by 25 (11 self)
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We present an extension of Logic Programming (LP) which, in addition to ordinary LP clauses, also includes integrity constraints, explicit representation of disjunction in the bodies of clauses and in goals, and suspension of atoms as in concurrent logic languages. The resulting framework aims to unify Constraint Logic Programming (CLP), Abductive Logic Programming (ALP) and Semantic Query Optimisation (SQO) in deductive databases. We present a proof procedure for the new framework, simplifying and generalising previously proposed proof procedures for ALP. We discuss applications of the framework, formulating traditional problems from LP, ALP, CLP and SQO.
Coherent Integration of Databases by Abductive Logic Programming
 Journal of Artificial Intelligence Research
, 2004
"... We introduce an abductive method for a coherent integration of independent datasources. ..."
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Cited by 17 (5 self)
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We introduce an abductive method for a coherent integration of independent datasources.