FORTE (First Order Revision of Theories from Examples) is a machine learning system for modifiying a first-order Horn-clause domain theory to fit a set of training examples. FORTE uses a hill-climbing approach to revise theories. It identifies possible errors in an input theory and calls on a library of operators to develop possible revisions. These operators are constructed from methods such as propositional theory refinement, first-order induction, and inversion resolution. To download and for more information, click here.