Workshop on Abduction and Induction in Ai and Scientific Modeling
Peter Flach, Antonis Kakas, Lorenzo Magnani, Oliver Ray
- Year
- 2006
- Citations
- 3
Abstract
ion, induction and abduction in scientific modelling D. Portides . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12 Disjunctive bottom set and its computation W. Lu and R. King . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16 Abduction, induction, and the logic of scientific knowledge development P. Flach, A. Kakas and O. Ray . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21 An abduction framework for handling incompleteness in first-order learning S. Ferilli, F. Esposito, N. Di Mauro, T. Basile and M. Biba . . . . . . . . . . . . . . . 24 Using abduction for induction of normal logic programs O. Ray . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28 Abduction, induction, and the robot scientist (invited talk abstract) R. King . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32
Keywords
Related papers
Statistical Learning Theory
Yuhai Wu, Vladimir Vapnik
1999
Artificial intelligence: a modern approach
1995
Fractional Differential Equations
Igor Podlubný
2025
Applied Nonlinear Control
Jean-Jacques Slotine, Weiping Li
1991