Utilizing symmetry in evolutionary design

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Title: Utilizing symmetry in evolutionary design
Author: Valsalam, Vinod K.
Abstract: Can symmetry be utilized as a design principle to constrain evolutionary search , making it more effective ? This dissertation aims to show that this is indeed the case , in two ways . First , an approach called ENSO is developed to evolve modular neural network controllers for simulated multilegged robots . Inspired by how symmetric organisms have evolved in nature , ENSO utilizes group theory to break symmetry systematically , constraining evolution to explore promising regions of the search space . As a result , it evolves effective controllers even when the appropriate symmetry constraints are difficult to design by hand . The controllers perform equally well when transferred from simulation to a physical robot . Second , the same principle is used to evolve minimal -size sorting networks . In this different domain , a different instantiation of the same principle is effective : building the desired symmetry step -by -step . This approach is more scalable than previous methods and finds smaller networks , thereby demonstrating that the principle is general . Thus , evolutionary search that utilizes symmetry constraints is shown to be effective in a range of challenging applications .
URI: http : / /hdl .handle .net /2152 /ETD -UT -2010 -08 -2021
Date: 2010-12-13


Utilizing symmetry in evolutionary design. Doctoral dissertation, University of Texas at Austin. Available electronically from http : / /hdl .handle .net /2152 /ETD -UT -2010 -08 -2021 .

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