6/4/2023 0 Comments Abduction definition![]() ![]() Implicit hitting set algorithms for reasoning beyond NP. In Neural Information Processing Systems 2017 (pp. In Proceedings of the ACL 2014 Workshop on Semantic Parsing (pp. Rocktäschel, T., Bošnjak, M., Singh, S., & Riedel, S. A theory of diagnosis from first principles. Kruse (Eds.), Handbook of Defeasible Reasoning and Uncertainty Management Systems (Vol. A shorter version is in: EPTCS online proceedings of ICLP (Vol. Enhancing linear algebraic computation of logic programs using sparse representation. In 2021 IEEE 33rd International Conference on Tools with Artificial Intelligence (ICTAI) (pp. ![]() Linear algebraic computation of propositional horn abduction. ![]() Solar: An automated deduction system for consequence finding. Nabeshima, H., Iwanuma, K., Inoue, K., & Ray, O. Robinson (Eds.), Handbook of Logic in Artificial Intelligence and Logic Programming (Vol. The role of abduction in logic programming. Abductive Inference: Computation, Philosophy, Technology. IfCoLog Journal of Logics and Their Applications, 3(1), 7–36. Sadri (Eds.), Computational Logic: Logic Programming and Beyond: Essays in Honour of Robert A. Linear resolution for consequence finding. In Proceedings of the AAAI Conference on Artificial Intelligence (Vol. Abduction-based explanations for machine learning models. Ignatiev, A., Narodytska, N., & Marques-Silva, J. In International Conference on Theory and Applications of Satisfiability Testing (pp. PySAT: A Python toolkit for prototyping with SAT oracles. Ignatiev, A., Morgado, A., & Marques-Silva, J. In ECAI 2016 (Frontiers in Artificial Intelligence and Applications, Vol. Propositional abduction with implicit hitting sets. A correction to the algorithm in Reiter’s theory of diagnosis. The stable model semantics for logic programming. SIAM Journal on Discrete Mathematics, 31(1), 63–100. The minimal hitting set generation problem: Algorithms and computation. In Proceedings of the 17th International Conference on Principles of Knowledge Representation and Reasoning (pp. Towards an inductive logic programming approach for explaining black-box preference learning systems. A., Spezialetti, M., Raggioli, L., & Rossi, S. In Neural Information Processing Systems 2019 (Vol. Bridging machine learning and logical reasoning by abductive learning. On the relationship between abduction and deduction. In ILP 2018 (CEUR Workshop Proceedings, Vol. Tensor-based abduction in horn propositional programs. New Generation Computing, 9, 335–364.Īspis, Y., Broda, K., & Russo, A. Compared with logical methods based on symbolic manipulation, the linear algebraic method has an advantage for efficient computation. For abduction, a similar technique is employed for multiplications of an abductive matrix and observation vectors, together with enumeration of minimal hitting sets by avoiding dimension explosion. The method is built on top of the fixed-point computation of matrix-vector multiplications for deduction in logic programming, where a matrix and vectors, respectively, represent a logic program and interpretations. This chapter summarizes the novel approach to use linear algebra for abduction in logic programming developed by the authors. Logic programming has been used for both representation languages and computational procedures for abductive computation. Abduction has been applied to various problems in many fields, and computing abductive explanations is an essential task in such applications. ![]()
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