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31
Abduction from Logic Programs: Semantics and Complexity
 Theoretical Computer Science
, 1998
"... Abduction from observations and a theory, find using hypotheses an explanation for the observations  gained increasing interest during the last years. This form of reasoning has wide applicability in different areas of computer science; in particular, it has been recognized as an important pr ..."
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Cited by 37 (7 self)
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Abduction from observations and a theory, find using hypotheses an explanation for the observations  gained increasing interest during the last years. This form of reasoning has wide applicability in different areas of computer science; in particular, it has been recognized as an important principle of commonsense reasoning. In this paper, we define a general abduction model for logic programming, where the inference operator (i.e., the semantics to be applied on programs), can be specified by the user. Advanced forms of logic programming have been proposed as valuable tools for knowledge representation and reasoning. We show that logic programming semantics can be more meaningful for abductive reasoning than classical inference by providing examples from the area of knowledge representation and reasoning. The main part of the paper is devoted to an extensive study of the computational complexity of the principal problems in abductive reasoning, which are: Given an inst...
Learning with Abduction
 In Proceedings of the 7th International Workshop on Inductive Logic Programming
, 1997
"... We investigate how abduction and induction can be integrated into a common learning framework through the notion of Abductive Concept Learning (ACL). ACL is an extension of Inductive Logic Programming (ILP) to the case in which both the background and the target theory are abductive logic programs a ..."
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Cited by 22 (6 self)
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We investigate how abduction and induction can be integrated into a common learning framework through the notion of Abductive Concept Learning (ACL). ACL is an extension of Inductive Logic Programming (ILP) to the case in which both the background and the target theory are abductive logic programs and where an abductive notion of entailment is used as the coverage relation. In this framework, it is then possible to learn with incomplete information about the examples by exploiting the hypothetical reasoning of abduction. The paper presents the basic framework of ACL with its main characteristics and illustrates its potential in addressing several problems in ILP such as learning with incomplete information and multiple predicate learning. An algorithm for ACL is developed by suitably extending the topdown ILP method for concept learning and integrating this with an abductive proof procedure for Abductive Logic Programming (ALP). A prototype system has been developed and applied to lea...
A Unifying View for Logic Programming with NonMonotonic Reasoning
, 1997
"... We provide a simple formulation of a framework where some extensions of logic programming with nonmonotonic reasoning are treated uniformly, namely two kinds of negation and abduction. The resulting semantics is purely modeltheoretic, and gives meaning to any noncontradictory abductive logic pr ..."
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Cited by 18 (11 self)
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We provide a simple formulation of a framework where some extensions of logic programming with nonmonotonic reasoning are treated uniformly, namely two kinds of negation and abduction. The resulting semantics is purely modeltheoretic, and gives meaning to any noncontradictory abductive logic program. Moreover, it embeds and generalizes some existing semantics which deal with negation and abduction. The framework is equipped with a correct topdown proof procedure. Keywords: Programming languages, Logic programming, Nonmonotonic reasoning, Negation, Abduction. Dipartimento di Informatica, Universit`a di Pisa, Corso Italia 40, Pisa, Italy. brogi@di.unipi.it y DEIS, Universit`a di Bologna, Viale Risorgimento 2, 40136 Bologna, Italy. elamma@deis.unibo.it z Dipartimento di Informatica, Universit`a di Pisa, Corso Italia 40, Pisa, Italy. paolo@di.unipi.it x DEIS, Universit`a di Ferrara, Via Saragat, 41100 Ferrara, Italy. pmello@ing.unife.it Contents 1 Introduction and Motiva...
ACLP: Integrating Abduction and Constraint Solving
 Journal of Logic Programming
, 2000
"... ACLP is a system which combines abductive reasoning and constraint solving by integrating the frameworks of Abductive Logic Programming (ALP) and Constraint Logic Programming (CLP). It forms a general highlevel knowledge representation environment for abductive problems in Artificial Intelligence an ..."
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Cited by 18 (2 self)
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ACLP is a system which combines abductive reasoning and constraint solving by integrating the frameworks of Abductive Logic Programming (ALP) and Constraint Logic Programming (CLP). It forms a general highlevel knowledge representation environment for abductive problems in Artificial Intelligence and other areas. In ACLP, the task of abduction is supported and enhanced by its nontrivial integration with constraint solving facilitating its application to complex problems. The ACLP system is currently implemented on top of the CLP language of ECLiPSe as a metainterpreter exploiting its underlying constraint solver for finite domains. It has been applied to the problems of planning and scheduling in order to test its computational effectiveness compared with the direct use of the (lower level) constraint solving framework of CLP on which it is built. These experiments provide evidence that the abductive framework of ACLP does not compromise significantly the computational efficiency of the solutions. Other experiments show the natural ability of ACLP to accommodate easily and in a robust way new or changing requirements of the original problem.
Abductive Concept Learning
, 1999
"... We investigate how abduction and induction can be integrated into a common learning framework. In particular, we consider an extension of Inductive Logic Programming (ILP) for the case in which both the background and the target theories are abductive logic programs and where an abductive notion ..."
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Cited by 16 (8 self)
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We investigate how abduction and induction can be integrated into a common learning framework. In particular, we consider an extension of Inductive Logic Programming (ILP) for the case in which both the background and the target theories are abductive logic programs and where an abductive notion of entailment is used as the basic coverage relation for learning. This extended learning framework has been called Abductive Concept Learning (ACL). In this framework, it is possible to learn with incomplete background information about the training examples by exploiting the hypothetical reasoning of abduction. We also study how the ACL framework can be used as a basis for multiple predicate learning. An algorithm for ACL is developed by suitably extending the topdown ILP method: the deductive proof procedure of Logic Programming is replaced by an abductive proof procedure for Abductive Logic Programming. This algorithm also incorporates a phase for learning integrity 2 Fabrizio...
The SOCS computational logic approach for the specification and verification of agent societies
 In Corrado Priami and Paola Quaglia, editors, Global Computing: IST/FET International Workshop, GC 2004 Rovereto, Italy, March 912, 2004 Revised Selected Papers, volume 3267 of Lecture Notes in Artificial Intelligence
, 2005
"... Abstract. This article summarises part of the work done during the first two years of the SOCS project, with respect to the task of modelling interaction amongst CLbased agents. It describes the SOCS social model: an agent interaction specification and verification framework equipped with a declara ..."
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Cited by 11 (7 self)
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Abstract. This article summarises part of the work done during the first two years of the SOCS project, with respect to the task of modelling interaction amongst CLbased agents. It describes the SOCS social model: an agent interaction specification and verification framework equipped with a declarative and operational semantics, expressed in terms of abduction. The operational counterpart of the proposed framework has been implemented and integrated in SOCSSI, a tool that can be used for onthefly verification of agent compliance with respect to specified protocols. 1
Specification and verification of interaction protocols: a computational logic approach based on abduction
, 2003
"... In this paper we propose a logicbased approach for the specification and verification of interaction protocols. We give the syntax of the proposed language, declarative and operational semantics of an abductive proof procedure for compliance verification. The proof procedure uses constraints for ef ..."
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Cited by 9 (9 self)
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In this paper we propose a logicbased approach for the specification and verification of interaction protocols. We give the syntax of the proposed language, declarative and operational semantics of an abductive proof procedure for compliance verification. The proof procedure uses constraints for efficiently dealing with largescale problems, and is implemented in Constraint Handling Rules. We give an example of specification and onthefly verification of compliance in a negotiation protocol. 1
An Implementation for Abductive Logic Agents
 Proceedings AI*IA99, Pitagora Editore
, 1999
"... This paper presents the distributed implementation of ALIAS, an architecture composed of several cooperating intelligent agents. This system is particularly suited to solve problems in cases where knowledge about the problem domain is incomplete and agents may need to form reasonable hypotheses. In ..."
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Cited by 8 (4 self)
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This paper presents the distributed implementation of ALIAS, an architecture composed of several cooperating intelligent agents. This system is particularly suited to solve problems in cases where knowledge about the problem domain is incomplete and agents may need to form reasonable hypotheses. In ALIAS agents are equipped with hypothetical reasoning capabilities, performed by means of abduction: if the knowledge available to a logic agent is insuffcient to solve a query, the agent could abduce new hypotheses. Each agent is characterized by a local knowledge base represented by an abductive logic program. Agents may differ in their knowledge bases, but must agree on assumed hypotheses. That global knowledge base is dynamically created and managed by means of a shared tuple space. The prototype, developed using Java and Prolog, can run on TCP/IP network of computers. In the paper, we also discuss some experimental results to evaluate prototype efficiency.
Eres  a system for reasoning about actions, events and observations
 In Baral, C., & Truszczynski, M. (Eds.), International Workshop on NonMonotonic Reasoning, Special Session on System Descriptions and Demonstration  NMR’2000
, 2000
"... ERES is a system that implements the Language E, a logic for reasoning about narratives of action occurrences and observations. E’s semantics is modeltheoretic, but this implementation is based on a sound and complete reformulation of E in terms of argumentation, and uses general computational tech ..."
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Cited by 7 (1 self)
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ERES is a system that implements the Language E, a logic for reasoning about narratives of action occurrences and observations. E’s semantics is modeltheoretic, but this implementation is based on a sound and complete reformulation of E in terms of argumentation, and uses general computational techniques of argumentation frameworks. The system derives sceptical nonmonotonic consequences of a given reformulated theory which exactly correspond to consequences entailed by E’s modeltheory. The computation relies on a complimentary ability of the system to derive credulous nonmonotonic consequences together with a set of supporting assumptions which is sufficient for the (credulous) conclusion to hold. ERES allows theories
Abduction with Hypotheses Confirmation
 In Proc. of the 19th Intl. Joint Conf. on Artificial Intelligence (IJCAI05
, 2004
"... Abduction can be seen as the formal inference corresponding to human hypothesis making. It typically has the purpose of explaining some given observation. In classical abduction, hypotheses could be made on events that may have occurred in the past. In general, abductive reasoning can be used to ..."
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Cited by 4 (2 self)
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Abduction can be seen as the formal inference corresponding to human hypothesis making. It typically has the purpose of explaining some given observation. In classical abduction, hypotheses could be made on events that may have occurred in the past. In general, abductive reasoning can be used to generate hypotheses about events possibly occurring in the future (forecasting), or may suggest further investigations that will confirm or disconfirm the hypotheses made in a previous step (as in scientific reasoning). We propose an operational framework based on Abductive Logic Programming, extending existing frameworks in many respects, including accommodating dynamic observations and hypothesis confirmation.