Abstract The motivation of the present study is to evolve virtual creatures in a diverse simulated 3D environment. The proposed scheme is based on the artificial evolution using the Neuro Evolution of Augmenting Topologies (NEAT) algorithm to educe a neural network that controls the muscle forces of the artificial creatures. The morphologies of the creatures are established using the Genetic Algorithm (GA) method based on the distance metrics fitness function. The concept of damaging crossover of neural networks and genetic language for the morphology of creatures has been considered in the morphologies of the artificial creature. Creatures with certain morphological traits consume a large time to optimize their kinetics, thus they are placed in a separate species to limit the search. The simulation results in the significant kinetics of artificial creatures (2-5 limbs) in virtual mediums with varying dynamic and static coefficients of friction (0.0-4.0). The motion of artificial creatures in the simulated medium was determined at different angles and demonstrated in the 3D space.

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[22] Ventrella J., “Attractiveness vs. Efficiency (How Mate Preference Affects Location in the Evolution of Artificial Swimming Organisms),” in Proceedings of the 6th International Conference on Artificial Life, Madison, pp. 178-186, 1998. Sunil Kumar Jha received the B.Sc. and M.Sc. degrees in Physics from VBS Purvanchal University, India, in 2003 and 2005, and Ph.D. in Physics from Banaras Hindu University, India, in 2012. His research interests include data mining and pattern recognition applications. Filip Josheski completed B.Sc. from Faculty of Machine Intelligence and Robotics, University of Information Science and Technology “St. Paul the Apostle, North Macedonia in 2015. His research interest includes data mining, machine learning and virtual creature. Xiaorui Zhang received Ph.D.at Southeast University, China, in 2010. She is a professor in Nanjing University of Information Science and Technology. She has published more than 50 papers in reputed journals. Her research interests include digital forensics, image processing the virtual reality and human-computer interaction. Zulfiqar Ahmad worked as Research Associate in Department of Environmental Sciences, University of California Riverside, USA. His research interested is in Machine learning and data mining application. He has published 33, SCI articles in well reputed international peer reviewed journals.