Quantitative measure of structural and geometric similarity of 3D morphologies



This work describes a new heuristic algorithm that estimates structural and geometric similarity of three-dimensional morphologies. It is an extension to previously developed measure of similarity (Komosinski et al., Theor Biosci 2001, 120, 271–286) that was only able to consider the structure of 3D constructs. Morphologies are modeled as graphs with vertices as points in a 3D space, and edges connecting these vertices. This model is very general, therefore the proposed algorithm can be applied in (and across) a number of disciplines including artificial life, evolutionary design, engineering, robotics, biology, and chemistry. The primary areas of application of this fast numerical similarity measure are artificial life and evolutionary design, where great numbers of morphologies result from simulated evolutionary processes, and both structural and geometric aspects are significant. Geometry of 3D constructs (i.e., locations of body parts in space) is as important as the structure (i.e., connections of body parts), because both determine behavior of creatures or designs and their fitness in a particular environment. In this work, both morphological aspects are incorporated in a single, highly discriminative measure of similarity. © 2011Wiley Periodicals, Inc. Complexity, 2011