Lexicographic Parsimony Pressure
GECCO '02 Proceedings of the Genetic and Evolutionary Computation Conference
Behavioral Diversity and a Probabilistically Optimal GP Ensemble
Genetic Programming and Evolvable Machines
Computational Statistics & Data Analysis
Difficulty of unimodal and multimodal landscapes in genetic programming
GECCO'03 Proceedings of the 2003 international conference on Genetic and evolutionary computation: PartII
A Field Guide to Genetic Programming
A Field Guide to Genetic Programming
Proceedings of the 14th annual conference companion on Genetic and evolutionary computation
Evolving a digital multiplier with the pushgp genetic programming system
Proceedings of the 15th annual conference companion on Genetic and evolutionary computation
Expressive genetic programming
Proceedings of the 15th annual conference companion on Genetic and evolutionary computation
A behavior-based analysis of modal problems
Proceedings of the 15th annual conference companion on Genetic and evolutionary computation
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Many potential target problems for genetic programming are modal in the sense that qualitatively different modes of response are required for inputs from different regions of the problem's domain. This paper presents a new approach to solving modal problems with genetic programming, using a simple and novel parent selection method called lexicase selection. It then shows how the differential performance of genetic programming with and without lexicase selection can be used to provide a measure of problem modality, and it argues that defining such a measure in this way is not as methodologically problematic as it may initially appear. The modality measure is illustrated through the analysis of genetic programming runs on a simple modal symbolic regression problem. This is a preliminary report that is intended in part to stimulate discussion on the significance of modal problems, methods for solving them, and methods for measuring the modality of problems. Although the core concepts in this paper are presented in the context of genetic programming, they are also relevant to applications of other forms of evolutionary computation to modal problems.