Research papers 
Journal Article
M. Komosinski and Kubiak, M., Quantitative measure of structural and geometric similarity of 3D morphologies, Complexity, vol. 16, pp. 40–52, 2011.
W. Jaskowski and Komosinski, M., The Numerical Measure of Symmetry for 3D Stick Creatures, Artificial Life Journal, vol. 14, pp. 425–443, 2008.
J. A. Pyles and Grossman, E. D., Neural adaptation for novel objects during dynamic articulation, Neuropsychologia, vol. 47, pp. 1261–1268, 2009.
M. Komosinski and Ulatowski, S., Multithreaded computing in evolutionary design and in artificial life simulations, The Journal of Supercomputing, vol. 73, pp. 2214–2228, 2017.
M. Komosinski, Mensfelt, A., Tyszka, J., and Goleń, J., Multi-agent simulation of benthic foraminifera response to annual variability of feeding fluxes, Journal of Computational Science, vol. 21, pp. 419–431, 2017.
I. Błądek, Komosinski, M., and Miazga, K., Mappism: formalizing classical and artificial life views on mind and consciousness, Foundations of Computing and Decision Sciences, vol. 44, pp. 55–99, 2019.
M. Komosinski, Kups, A., Leszczyńska-Jasion, D., and Urbański, M., Identifying efficient abductive hypotheses using multi-criteria dominance relation, ACM Transactions on Computational Logic, vol. 15, pp. 28:1–28:20, 2014.
M. Komosinski and Ulatowski, S., Genetic mappings in artificial genomes, Theory in Biosciences, vol. 123, pp. 125–137, 2004.
M. Komosinski, The Framsticks system: versatile simulator of 3D agents and their evolution, Kybernetes: The International Journal of Systems & Cybernetics, vol. 32, pp. 156–173, 2003.
M. Hapke and Komosinski, M., Evolutionary Design of Interpretable Fuzzy Controllers, Foundations of Computing and Decision Sciences, vol. 33, pp. 351–367, 2008.
M. Komosinski, Koczyk, G., and Kubiak, M., On estimating similarity of artificial and real organisms, Theory in Biosciences, vol. 120, pp. 271–286, 2001.
M. Komosinski and Miazga, K., Comparison of the tournament-based convection selection with the island model in evolutionary algorithms, Journal of Computational Science, vol. 32, pp. 106–114, 2018.
M. Komosinski and Rotaru-Varga, A., Comparison of different genotype encodings for simulated 3D agents, Artificial Life Journal, vol. 7, pp. 395–418, 2001.
J. A. Pyles, Garcia, J. O., Hoffman, D. D., and Grossman, E. D., Brain activity evoked by perception of novel "biological motion", Journal of Vision, vol. 6, pp. 794–794, 2006.
M. Komosinski, Applications of a similarity measure in the analysis of populations of 3D agents, Journal of Computational Science, vol. 21, pp. 407–418, 2017.
Conference Paper
E. Spaak and Haselager, P. F. G., Imitation and mirror neurons: an evolutionary robotics model, in BNAIC 2008: 20th Belgian-Dutch Conference on Artificial Intelligence, Enschede, 2008.
M. Komosinski and Ulatowski, S., Framsticks: sztuczne życie – złożona symulacja stworzeń i ich ewolucji, in Materiały konferencyjne III Krajowej Konferencji Algorytmy Ewolucyjne i Optymalizacja Globalna KAEiOG (Proceedings of the National Conference on Evolutionary Computation and Global Optimization), Potok Złoty, 1999, pp. 157–166.
M. Komosinski and Ulatowski, S., Framsticks – Artificial Life, in ECML 98 Demonstration and Poster Papers, Chemnitz, 1998, pp. 7–9.
M. Komosinski and Mensfelt, A., A Flexible Dissimilarity Measure for Active and Passive 3D Structures and Its Application in the Fitness–Distance Analysis, in Applications of Evolutionary Computation, 2019.
K. Basiukajc, Komosinski, M., and Miazga, K., Fitness Diversification in the Service of Fitness Optimization: a Comparison Study, in Genetic and Evolutionary Computation Conference Companion (GECCO '22), Boston, USA, 2022.
M. Komosinski and Polak, J., Evolving free-form stick ski jumpers and their neural control systems, in Proceedings of the National Conference on Evolutionary Computation and Global Optimization, Poland, 2009, p. 103--110.
M. Komosinski and Miazga, K., Diversity control in evolution of movement, in Artificial Life Conference Proceedings, 2021.
A. Klejda, Komosinski, M., and Mensfelt, A., Diversification Techniques and Distance Measures in Evolutionary Design of 3D Structures, in Genetic and Evolutionary Computation Conference Companion (GECCO '22), Boston, USA, 2022.
A. Gajda, Kups, A., and Urbański, M., A connectionist approach to abductive problems: employing a learning algorithm, in Proceedings of the 2016 Federated Conference on Computer Science and Information Systems (FedCSIS), 2016, pp. 353–362.
P. Kaszuba, Komosinski, M., and Mensfelt, A., Automated development of latent representations for optimization of sequences using autoencoders, in 2021 IEEE Congress on Evolutionary Computation (CEC), 2021.

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