Michael van Lent
Constructive induction techniques use constructors to combine existing features into new features. Usually the goal is to improve the accuracy and/or efficiency of classification. An alternate use of new features is to create representations which allow planning in more efficient state spaces. An inefficient state space may be too fine grained, requiring deep search for plans with many steps, may be too fragmented, requiring separate plans for similar cases, or may be unfocused, resulting in poorly directed search. Modifying the representation with constructive induction can improve the state space and overcome these inefficiencies. Additionally, since most learning systems depend on good domain features, constructive induction will compliment the action of other algorithms.