<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Maciej Komosinski</style></author><author><style face="normal" font="default" size="100%">Marek Kubiak</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Quantitative measure of structural and geometric similarity of 3D morphologies</style></title><secondary-title><style face="normal" font="default" size="100%">Complexity</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2011</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.framsticks.com/files/common/Komosinski_Kubiak_MeasureSimilarity3DMorphologies.pdf</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">6</style></number><publisher><style face="normal" font="default" size="100%">Wiley</style></publisher><volume><style face="normal" font="default" size="100%">16</style></volume><pages><style face="normal" font="default" size="100%">40–52</style></pages><abstract><style face="normal" font="default" size="100%">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., 2001) 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.</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Maciej Komosinski</style></author><author><style face="normal" font="default" size="100%">Grzegorz Koczyk</style></author><author><style face="normal" font="default" size="100%">Marek Kubiak</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">On estimating similarity of artificial and real organisms</style></title><secondary-title><style face="normal" font="default" size="100%">Theory in Biosciences</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">AL</style></keyword><keyword><style  face="normal" font="default" size="100%">Biology</style></keyword><keyword><style  face="normal" font="default" size="100%">EA</style></keyword><keyword><style  face="normal" font="default" size="100%">Theory</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2001</style></year><pub-dates><date><style  face="normal" font="default" size="100%">December</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.framsticks.com/files/common/Komosinski_Similarity_TheoryInBiosc2001.pdf</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">3-4</style></number><volume><style face="normal" font="default" size="100%">120</style></volume><pages><style face="normal" font="default" size="100%">271–286</style></pages><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>6</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Maciej Komosinski</style></author><author><style face="normal" font="default" size="100%">Marek Kubiak</style></author></authors><secondary-authors><author><style face="normal" font="default" size="100%">Jozef Kelemen</style></author><author><style face="normal" font="default" size="100%">Petr Sosík</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">Taxonomy in Alife. Measures of similarity for complex artificial organisms</style></title><secondary-title><style face="normal" font="default" size="100%">Advances in Artificial Life. Lecture Notes in Artificial Intelligence 2159</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Agents</style></keyword><keyword><style  face="normal" font="default" size="100%">AL</style></keyword><keyword><style  face="normal" font="default" size="100%">Biology</style></keyword><keyword><style  face="normal" font="default" size="100%">EA</style></keyword><keyword><style  face="normal" font="default" size="100%">Simulation</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2001</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.framsticks.com/files/common/Komosinski_TaxonomyAlife_ECAL2001.pdf</style></url></web-urls></urls><publisher><style face="normal" font="default" size="100%">Springer-Verlag</style></publisher><pages><style face="normal" font="default" size="100%">685–694</style></pages><language><style face="normal" font="default" size="100%">eng</style></language></record></records></xml>