Evolving Controller Symmetry for Multilegged Robots (2010)
Author: Vinod Valsalam
The videos linked below demonstrate the walking behaviors evolved by five neuroevolution methods, which differ only in the way they determine controller symmetry: (1) Evolving symmetry systematically using ENSO, (2) evolving symmetry randomly without using the group-theory mechanisms of ENSO, (3) using fixed S4 symmetry during evolution (i.e. maximal symmetry), (4) using fixed D2 symmetry during evolution, and (5) using direct encoding without symmetry constraints (which is equivalent to using the fixed trivial symmetry during evolution). The videos linked below demonstrate the walking behaviors evolved by five neuroevolution methods, which differ only in the way they determine controller symmetry: (1) Evolving symmetry systematically using ENSO, (2) evolving symmetry randomly without using the group-theory mechanisms of ENSO, (3) using fixed S4 symmetry during evolution (i.e. maximal symmetry), (4) using fixed D2 symmetry during evolution, and (5) using direct encoding without symmetry constraints (which is equivalent to using the fixed trivial symmetry during evolution).

Demo website
Vinod Valsalam Ph.D. Alumni vkv [at] alumni utexas net
Risto Miikkulainen Faculty risto [at] cs utexas edu
Evolving Symmetric and Modular Neural Network Controllers for Multilegged Robots Vinod K. Valsalam and Risto Miikkulainen In xploring New Horizons in Evolutionary Design of Robots: Workshop at the 2009 IEEE/RSJ Internat... 2009

Evolving Symmetric and Modular Neural Networks for Distributed Control Vinod K. Valsalam and Risto Miikkulainen In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO), 731--738, 200... 2009

Modular Neuroevolution for Multilegged Locomotion Vinod K. Valsalam and Risto Miikkulainen In Proceedings of the Genetic and Evolutionary Computation Conference GECCO 2008, 265-272, Ne... 2008

Utilizing Symmetry in Evolutionary Design Vinod Valsalam PhD Thesis, Department of Computer Sciences, The University of Texas at Austin, Austin, TX, 2010. Te... 2010

IJCNN-2013 Tutorial on Evolution of Neural Networks Risto Miikkulainen To Appear In 2013. Tutorial slides.. 2013

ENSO This package contains software implementing the ENSO approach for evolving symmetric modular neural networks. It also in... 2010