Neuroevolution of Actively Controlled Virtual Characters
Master thesis
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http://hdl.handle.net/11250/2454827Utgivelsesdato
2017Metadata
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Sammendrag
Physics-based character animation offer an attractive alternative to traditional animation
techniques, however, physics-based approaches often struggle to incorporate active user
control of these characters. This thesis suggests a different approach to the problem of
actively controlled virtual characters. The proposed solution takes a neuroevolutionary
approach, using HyperNEAT to evolve neural controllers for a simulated eight-legged
character, a previously untested character morphology for this algorithm. Using these
controllers this thesis aims to evaluate the robustness and responsiveness of a control
strategy that changes between them based on simulated user input. The results show that
HyperNEAT is quite capable of evolving long walking controllers for this character, but
also suggests a need for further refinement when operated in tandem.
Beskrivelse
Master's thesis Information- and communication technology IKT590 - University of Agder 2017