Evolution of Parallel Cellular Machines. The Cellular Programming Approach

Description

Preface......Page 2 Contents......Page 6 Prologue......Page 9 Cellular Automata......Page 11 Genetic Algorithms......Page 20 Introduction......Page 23 Universal 2-State, 5-Neighbor Non-Uuniform CA......Page 24 Reducing the Number of Rules......Page 30 Implementing Universal Machine using Finite Configuration......Page 31 Quasi-Uniform Cellular Space......Page 33 Discussion......Page 35 Introduction......Page 38 The ALife Model......Page 40 Multicellularity......Page 42 Evolution......Page 51 Discussion......Page 74 Introduction......Page 79 Previous Work......Page 81 Cellular Programming Algorithm......Page 85 Results using 1D, r=3 Grids......Page 88 Results using 1D, r=1 Grids......Page 89 Results using 2D, 5-Neighbor Grids......Page 100 Scaling Evolved CAs......Page 102 Discussion......Page 104 Applications of Cellular Programming......Page 107 Ordering Task......Page 108 Rectangle-Boundary Task......Page 111 Thinning Task......Page 113 Random Number Generation......Page 117 Concluding Remarks......Page 123 Introduction......Page 124 Large-Scale Programmable Circuits......Page 126 Implementing Evolware......Page 127 Concluding Remarks......Page 131 Introduction......Page 133 Faults & Damage in Lattice Models......Page 134 Probabilistic Faults in CA......Page 135 Results......Page 136 Concluding Remarks......Page 143 Introduction......Page 145 Architecture Considerations......Page 146 Fixed Architectures......Page 149 Evolving Architectures......Page 152 Evolving Low-Cost Architectures......Page 157 Discussion......Page 158 Concluding Remarks & future Research......Page 162 Growth & Replication - Rules Specification......Page 168 2-State, r=1 CA that classifies Density......Page 171 Specification of Evolved CAs......Page 174 Specification of Evolved Architecture......Page 176 Computing acd & equivalent d'......Page 178 Biblio......Page 179 Index......Page 195