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This paper considers the following induction problem. Given the background knowledge Band an observation O, find a hypothesis Hsuch that a consistent theory B茂戮驴 Hhas a minimal model satisfying O. We call this type of induction brave induction. Brave induction is different from explanatory induction in ILP, which requires that Ois satisfied in every model of B茂戮驴 H. Brave induction is useful for learning disjunctiverules from observations, or learning from the background knowledge containing indefinite or incomplete information. We develop an algorithm for computing brave induction, and extend it to induction in answer set programming.