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(2017) Springer handbook of model-based science, Dordrecht, Springer.
Inductive generalization is a defeasible type of inference which we use to reason from the particular to the universal. First, a number of systems are presented that provide different ways of implementing this inference pattern within first-order logic. These systems are defined within the adaptive logics framework for modeling defeasible reasoning. Next, the logics are re-interpreted as criteria of confirmation. It is argued that they withstand the comparison with two qualitative theories of confirmation, Hempel's satisfaction criterion and hypothetico-deductive confirmation.
Publication details
DOI: 10.1007/978-3-319-30526-4_11
Full citation:
Beirlaen, M. (2017)., Qualitative inductive generalization and confirmation, in L. Magnani & T. Bertolotti (eds.), Springer handbook of model-based science, Dordrecht, Springer, pp. 231-248.