BibSonomy publications for /user/diego_ma/abductionFri Dec 14 02:44:58 CET 2007Submitted to \emph{Theory and Practice of Logic Programming}Abductive Logic Programs with Penalization: Semantics, Complexity and Implementation2003abduction Abduction, first proposed in the setting of classical logics, has been studied with growing interest in the logic programming area during the last years. In this paper we study \emph{abduction with penalization} in the logic programming framework. This form of abductive reasoning, which has not been previously analyzed in logic programming, turns out to represent several relevant problems, including optimization problems, very naturally. We define a formal model for abduction with penalization over logic programs, which extends the abductive framework proposed by Kakas and Mancarella. We address knowledge representation issues, encoding a number of problems in our abductive framework. In particular, we consider some relevant problems, taken from different domains, ranging from optimization theory to diagnosis and planning; their encodings turn out to be simple and elegant in our formalism. We thoroughly analyze the computational complexity of the main problems arising in the context of abduction with penalization from logic programs. Finally, we implement a system supporting the proposed abductive framework on top of the DLV engine. To this end, we design a translation from abduction problems with penalties into logic programs with weak constraints. We prove that this approach is sound and complete.Fri Dec 14 02:44:11 CET 2007Working Notes of the {IJCAI}-97 Workshop on Abduction and Induction in {AI}Integrating Abduction in Machine Learning1997abduction induction Fri Dec 14 02:40:41 CET 2007Artificial Intelligence69-142Interpretation as Abduction631993abduction NLP Fri Dec 14 02:40:33 CET 2007The Origin and Evolution of Language: A Plausible, Strong-{AI} Account1996evolution reification abduction No abstractFri Dec 14 02:39:58 CET 2007Proc. AAAI Fall Symposium on Question Answering Systems63-71Finding Answers in Large Collections of Texts: Paragraph Indexing + Abductive Inference1999question_answering abduction This paper describes a methodology of answering questions by using information retrieved from very large collections of texts. We argue that combinations of information retrieval and extractions techniques cannot be used, due to the open-domain nature of the task. We propose a solution based on indexing techniques that identify paragraphs from texts where the answers can be found. The validity of the answers is obtained through a lightweight process of abduction.