Abstract
This chapter aims to develop a logical account of inductive reasoning, one of the most important ways to synthesise new knowledge. Induction provides an idealised model for empirical sciences, where one aims to develop general theories that account for phenomena observed in controlled experiments. It also provides an idealised model for cognitive processes such as learning concepts from instances. The advent of the computer has suggested new inductive tasks such as program synthesis from examples of input-output behaviour and knowledge discovery in databases, and the application of inductive methods to artificial intelligence problems is an active research area, which has displayed considerable progress over the last decades.
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Flach, P.A. (2000). Logical Characterisations of Inductive Learning. In: Gabbay, D.M., Kruse, R. (eds) Abductive Reasoning and Learning. Handbook of Defeasible Reasoning and Uncertainty Management Systems, vol 4. Springer, Dordrecht. https://doi.org/10.1007/978-94-017-1733-5_4
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DOI: https://doi.org/10.1007/978-94-017-1733-5_4
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