Multistrategy theory revision: Induction and abduction in INTHELEX

This paper presents an integration of induction and abduction in INTHELEX, a prototypical incremental learning system. The refinement operators perfor m theory revision in a search space whose structure is induced by a quasi-o rdering, derived from Plotkin's theta-subsumption, compliant with the princ iple of Object Identity. A reduced complexity of the refinement is obtained , without a major loss in terms of expressiveness. These inductive operator s have been proven ideal for this search space. Abduction supports the indu ctive operators in the completion of the incoming new observations. Experim ents have been run on a standard dataset about family trees as well as in t he domain of document classification to prove the effectiveness of such mul tistrategy incremental learning system with respect to a classical batch al gorithm.