Using convex hulls to represent classifier conditions

This papers presents a novel representation of classifier conditions based on convex hulls. A classifier condition is represented by a sets of points in the problem space. These points identify a convex hull that delineates a convex region in the problem space. The condition matches all the problem instances inside such region. XCSF with convex conditions is applied to function approximation problems and its performance is compared to that of XCSF with interval conditions. The comparison shows that XCSF with convex hulls converges faster than XCSF with interval conditions. However, convex conditions usually do not produce more compact solutions. Categories and Subject Descriptors

• Type: Conference
• Year: 2006
• Where: GECCO
• Authors: Pier Luca Lanzi, Stewart W. Wilson
• Keywords: Classifier Condition, Convex Conditions, Convex Hulls, GECCO 2006, Optimization