<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Kaszuba, Piotr</style></author><author><style face="normal" font="default" size="100%">Komosinski, Maciej</style></author><author><style face="normal" font="default" size="100%">Mensfelt, Agnieszka</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Automated development of latent representations for optimization of sequences using autoencoders</style></title><secondary-title><style face="normal" font="default" size="100%">2021 IEEE Congress on Evolutionary Computation (CEC)</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2021</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.framsticks.com/files/common/LatentRepresentationsForSequencesOptimization.pdf</style></url></web-urls></urls><publisher><style face="normal" font="default" size="100%">IEEE</style></publisher><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">In this paper, we propose an automated method for the development of new representations of sequences. For this purpose, we introduce a two-way mapping from variable length sequence representations to a latent representation modelled as the bottleneck of an LSTM (long short-term memory) autoencoder. Desirable properties of such mappings include smooth fitness landscapes for optimization problems and better evolvability. This work explores the capabilities of such latent encodings in the context of optimization of 3D structures. Various improvements are adopted that include manipulating the autoencoder architecture and its training procedure. The results of evolutionary algorithms that use different variants of automatically developed encodings are compared.</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></authors></contributors><titles><title><style face="normal" font="default" size="100%">Applications of a similarity measure in the analysis of populations of 3D agents</style></title><secondary-title><style face="normal" font="default" size="100%">Journal of Computational Science</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2017</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.framsticks.com/files/common/SimilarityPopulations3DAgents.pdf</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">21</style></volume><pages><style face="normal" font="default" size="100%">407–418</style></pages><abstract><style face="normal" font="default" size="100%">Research in complex collective and multi-agent systems often involves building models of three-dimensional biological life or evolving such structures in virtual environments. Applications stemming from evolutionary design, engineering, robotics, and artificial life require processing of large numbers of such agents that are encoded in some form of a &quot;genotype&quot;. However, what is important in evaluation is the &quot;phenotype&quot;, i.e. the actual 3D body and its properties. This work introduces a number of ways in which a measure of similarity of 3D agents can support researchers in recognizing the link between the genotype and phenotype spaces, building taxonomies of 3D bodies and automatically selecting representative agents. The measure of similarity employed here is based on phenotypes and places few restrictions on the compared designs, so it can be applied independently of genetic representation.</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>5</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Maciej Komosinski</style></author><author><style face="normal" font="default" size="100%">Agnieszka Mensfelt</style></author><author><style face="normal" font="default" size="100%">Topa, Paweł</style></author><author><style face="normal" font="default" size="100%">Jarosław Tyszka</style></author></authors><secondary-authors><author><style face="normal" font="default" size="100%">Gruca, Aleksandra</style></author><author><style face="normal" font="default" size="100%">Brachman, Agnieszka</style></author><author><style face="normal" font="default" size="100%">Kozielski, Stanisław</style></author><author><style face="normal" font="default" size="100%">Czachórski, Tadeusz</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">Application of a morphological similarity measure to the analysis of shell morphogenesis in Foraminifera</style></title><secondary-title><style face="normal" font="default" size="100%">Man–Machine Interactions 4</style></secondary-title><tertiary-title><style face="normal" font="default" size="100%">Advances in Intelligent Systems and Computing</style></tertiary-title></titles><dates><year><style  face="normal" font="default" size="100%">2016</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.framsticks.com/files/common/ForaminiferaGenotypePhenotypeMapping.pdf</style></url></web-urls></urls><publisher><style face="normal" font="default" size="100%">Springer</style></publisher><volume><style face="normal" font="default" size="100%">391</style></volume><pages><style face="normal" font="default" size="100%">215–224</style></pages><isbn><style face="normal" font="default" size="100%">978-3-319-23436-6</style></isbn><abstract><style face="normal" font="default" size="100%">This work evaluates the genotype-to-phenotype mapping defined by one of the models of growth of foraminifera. Foraminifera are simple unicellular organisms with very diverse morphologies. To analyze the mapping, a morphological similarity measure is needed that compares 3D structures. One of the key components of the similarity estimation algorithm is Singular Value Decomposition (SVD). Since this algorithm is heavily used and its performance is important, four SVD implementations have been compared in this work. Distance matrices of the phenotypes obtained for equally distant genotypes were computed using the similarity measure. For the visualization of the phenotype space, multidimensional scaling techniques were used. Visual comparison of the genotype and the phenotype spaces revealed characteristics and potential weaknesses of the analyzed model of foraminifera growth, and demonstrated usefulness of the proposed approach.</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>6</ref-type><contributors><secondary-authors><author><style face="normal" font="default" size="100%">Andrew Adamatzky</style></author><author><style face="normal" font="default" size="100%">Maciej Komosinski</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">Artificial Life Models in Hardware</style></title></titles><dates><year><style  face="normal" font="default" size="100%">2009</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.springer.com/978-1-84882-529-1</style></url></web-urls></urls><publisher><style face="normal" font="default" size="100%">Springer</style></publisher><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Hopping, climbing and swimming robots, nano-size neural networks, motorless walkers, slime mould and chemical brains – this book offers unique designs and prototypes of life-like creatures in conventional hardware and hybrid bio-silicon systems. Ideas and implementations of living phenomena in non-living substrates cast a colourful picture of state-of-the-art advances in hardware models of artificial life. Focusing on topics and areas based on non-traditional thinking, and new and emerging paradigms in bio-inspired robotics, this book has a unifying theme: the design and real-world implementation of artificial life robotic devices. Students and researchers will find this coverage of topics such as robotic energy autonomy, multi-locomotion of robots, biologically inspired autonomous robots, evolution in colonies of robotic insects, neuromorphic analog devices, self-configurable robots, and chemical and biological controllers for robots, will considerably enhance their understanding of the issues involved in the development of not-traditional hardware systems at the cusp of artificial life and robotics.</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>6</ref-type><contributors><secondary-authors><author><style face="normal" font="default" size="100%">Maciej Komosinski</style></author><author><style face="normal" font="default" size="100%">Andrew Adamatzky</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">Artificial Life Models in Software</style></title></titles><dates><year><style  face="normal" font="default" size="100%">2009</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.springer.com/978-1-84882-284-9</style></url></web-urls></urls><edition><style face="normal" font="default" size="100%">second</style></edition><publisher><style face="normal" font="default" size="100%">Springer</style></publisher><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Artificial Life Models in Software provides an introduction and guide to modern software tools for modeling and simulating life-like phenomena, written by those who personally design and develop software, hardware, and art installations in artificial life, simulated complex systems and virtual worlds. This timely volume offers a nearly exhaustive overview and original analysis of major non-profit software packages that are actively developed and supported by experts in artificial life and software design. The carefully selected topics include: simulation and evolution of real and artificial life forms, natural and artificial morphogenesis, self-organization, models of communication and social behaviors, emergent collective behaviors and swarm intelligence, agent-based simulations, autonomous and evolutionary robotics, adaptive, complex and biologically inspired ecosystems, artificial chemistries, and creative computer art. The models of life presented here are essential components in undergraduate and post-graduate courses in complex adaptive systems, multi-agent systems, collective robotics and nature-inspired computing. Readers interested in artificial life, evolutionary biology, simulation, cybernetics, computer graphics and animation, neuroscience, cognitive science, and philosophy will find this monograph a valuable guide and an excellent resource for supplementary reading.</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>6</ref-type><contributors><secondary-authors><author><style face="normal" font="default" size="100%">Andrew Adamatzky</style></author><author><style face="normal" font="default" size="100%">Maciej Komosinski</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">Artificial Life Models in Software</style></title></titles><dates><year><style  face="normal" font="default" size="100%">2005</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.springer.com/978-1-84882-284-9</style></url></web-urls></urls><edition><style face="normal" font="default" size="100%">first</style></edition><publisher><style face="normal" font="default" size="100%">Springer</style></publisher><pub-location><style face="normal" font="default" size="100%">New York</style></pub-location><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>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Maciej Hapke</style></author><author><style face="normal" font="default" size="100%">Maciej Komosinski</style></author><author><style face="normal" font="default" size="100%">Dawid Waclawski</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Application of Evolutionarily Optimized Fuzzy Controllers for Virtual Robots</style></title><secondary-title><style face="normal" font="default" size="100%">Proceedings of the 7th Joint Conference on Information Sciences</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2003</style></year><pub-dates><date><style  face="normal" font="default" size="100%">September</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.framsticks.com/files/common/EvolvedFuzzyControl_CINC2003.pdf</style></url></web-urls></urls><publisher><style face="normal" font="default" size="100%">Association for Intelligent Machinery</style></publisher><pub-location><style face="normal" font="default" size="100%">North Carolina, USA</style></pub-location><pages><style face="normal" font="default" size="100%">1605–1608</style></pages><language><style face="normal" font="default" size="100%">eng</style></language></record></records></xml>