<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>27</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Krzysztof Gorgolewski</style></author><author><style face="normal" font="default" size="100%">Maciej Komosinski</style></author><author><style face="normal" font="default" size="100%">Konrad Miazga</style></author><author><style face="normal" font="default" size="100%">Krzysztof Rosinski</style></author><author><style face="normal" font="default" size="100%">Paweł Rychły</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Properties of movement of 3D agents</style></title></titles><dates><year><style  face="normal" font="default" size="100%">2019</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.framsticks.com/files/common/PropertiesOfMovementOf3DAgents.pdf</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">RA-1/2019</style></number><publisher><style face="normal" font="default" size="100%">Poznan University of Technology, Institute of Computing Science</style></publisher><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>27</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Maciej Komosinski</style></author><author><style face="normal" font="default" size="100%">Krzysztof Rosinski</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Estimating similarity of neural network dynamics</style></title></titles><dates><year><style  face="normal" font="default" size="100%">2010</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.framsticks.com/files/common/SimilarityNeuralNetworkDynamics.pdf</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">RA-10/10</style></number><publisher><style face="normal" font="default" size="100%">Poznan University of Technology, Institute of Computing Science</style></publisher><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">This report concerns estimation of the similarity between neural networks of any topology. Motivations and benefits of having an automated and quantitative network comparison mechanism are presented. The concept of neural network dynamics (neuron output signal) is considered. A measure is proposed for estimating similarity of active (i.e., working) neural networks. Properties of the measure are analyzed theoretically and verified empirically. The experiments have been performed on a set of evolved networks responsible for controlling 3D structures (agents, robots). These experiments demonstrate the capabilities and the limitations of the proposed measure as a mechanism to support humans in analyzing large sets of neural networks.</style></abstract></record></records></xml>