EvoDebate Statement September 2001 Wolfgang Banzhaf Universität Dortmund, Informatik XI

W. Banzhaf - LS XI, FB Informatik, Universität Dortmund 2 Overview Extending the paradigm –Methods or Approaches –Theory –Applications

W. Banzhaf - LS XI, FB Informatik, Universität Dortmund 3 Extending the Paradigm Evolutionary Computation –Simplest approaches were introduced first –Simplest models were studied first –Toy problems were applied first Possible routes to extension –Riding the Technology wave –Problems in Science etc. are demanding –AL/AC, MC, QC, ER,...

W. Banzhaf - LS XI, FB Informatik, Universität Dortmund 4 EC - From Simple to Complicated Methods –GA: From bits to everything –ES: From real numbers to various representations –EP: From FSA to other representations –GP: From trees to all kinds of structures Theory –Schema Inequality (GA) to Schema equation –Spherical mutation rates (ES) to mutation ellipsoid Application –Regression Problem (GP) to classification and prediction –Parameter Optimization (GA/ES) to Multi-objective Opt.

W. Banzhaf - LS XI, FB Informatik, Universität Dortmund 5 Where to go from here? Riding the technology wave –Moore‘s Law –Distributed Networks –Scientific Progress Problems are demanding –Automatic Development of Scientific Models –Design Process for all Sorts of Devices –Complexity of Control New Arrivals –AL – AC –MC –QC –ER

W. Banzhaf - LS XI, FB Informatik, Universität Dortmund 6 Breeding of Algorithms and Machines Possible to breed (presently) Simple programs (GP) Electrical circuits (GP) Molecular machines (proteins) (Evolution in-vitro) Strains of bacteria (in-vitro, artificial selection) Organs (in-vitro) Not possible to breed presently Robots (hardware) Other real macroscopic machines

W. Banzhaf - LS XI, FB Informatik, Universität Dortmund 7 Problems What representation to choose? –Substrate for evolution –Operators able to work on the substrate How to reach universal formability of the underlying substrate (matter, structures)? –Developmental process of biology –Self-assembly, Self-organization How to code complex functions into „fitness“ for breeding? –Explicit vs. implicit fitness –Pre-structuring (time-scale separation, e.g. evolutionary and adaptive)