The Art and Science of Interface and Interaction Design (Vol. 1) (Studies in Computational Intelligence (141))

artists And Creators In Interactive Art And Interaction Design Have Long Been Conducting Research On Human-machine Interaction. Through Artistic, Conceptual, Social And Critical Projects, They Have Shown How Interactive Digital Processes Are Essential Elements For Their Artistic Creations. Resulting Prototypes Have Often Reached Beyond The Art Arena Into Areas Such As Mobile Computing, Intelligent Ambiences, Intelligent Architecture, Fashionable Technologies, Ubiquitous Computing And Pervasive Gaming. Many Of The Early Artist-developed Interactive Technologies Have Influenced New Design Practices, Products And Services Of Today's Media Society. This Book Brings Together Key Theoreticians And Practitioners Of This Fields. It Shows How Historically Relevant The Issues Of Interaction And Interface Design Are, As They Can Be Analyzed Not Only From An Engineering Point Of View But From A Social, Artistic And Conceptual, And Even Commercial Angle As Well. front-matter......Page 1 Introduction......Page 10 Basic DE Research......Page 14 The Control Variables Np, F, and Cr......Page 15 Diversity Enhancement......Page 16 Problem Domain Specific Research......Page 24 Objective Functions with Single Objective......Page 25 Combinatorial Problems......Page 27 Design Centering......Page 30 Time-Variant Objective Functions......Page 32 An Example: Digital Filter Design......Page 33 More Topics and Outlook......Page 35 References......Page 36 Background......Page 41 Classic DE......Page 42 Decomposability and the Role of Cr......Page 44 The DE/ran/1/either-or Algorithm......Page 45 Drift Bias in DE’s Generating Function......Page 48 The Mutation Distribution M......Page 49 The Three-Vector Recombination Distribution R......Page 51 Naturally Distributed K......Page 55 Computing $E(S^{(\mu)})$......Page 58 Computing $E(S{^(X^3)})$......Page 60 Drift-Free Selection......Page 61 Drift-Free DE......Page 62 The Test Bed: Scalable Benchmark Functions......Page 65 Measuring Performance......Page 70 Discussion of Results......Page 71 Population Size......Page 91 Mutation Probability......Page 92 Default Control Parameter Settings......Page 93 Drift-Free DE’s Benefits......Page 94 References......Page 95 Introduction......Page 97 The Original DE Algorithm......Page 98 The Self-Adaptive Control Parameters in a jDE Algorithm......Page 99 The SA-DE Algorithm......Page 100 Experimental Results......Page 101 Discussion......Page 115 References......Page 116 Appendix......Page 118 Introduction......Page 119 Differential Evolution......Page 121 Improvement-Based Criteria......Page 124 Movement-Based Criteria......Page 125 Distribution-Based Criteria......Page 126 Combined Criteria......Page 127 Experimental Settings......Page 128 Criterion ImpAv......Page 131 Criterion NoAcc......Page 134 Criterion MaxDistQuick......Page 135 Criterion StdDevQuick......Page 138 Criterion Diff......Page 141 Conclusions......Page 142 References......Page 144 Introduction......Page 147 Constraint Violation and -Level Comparison......Page 149 The Properties of the Constrained Method......Page 150 Differential Evolution......Page 151 The Algorithm of the $\varepsilon$DE......Page 152 Controlling the $\varepsilon$-Level......Page 153 Test Problems and Experimental Conditions......Page 154 Experimental Results......Page 156 Comparison with the Stochastic Ranking Method......Page 159 References......Page 160 Introduction......Page 163 Opposition-Based Optimization......Page 165 Opposition-Based Population Initialization......Page 167 Opposition-Based Generation Jumping......Page 169 Comparison of DE and ODE......Page 171 Contribution of Opposite Points......Page 172 ODE with Variable Jumping Rate......Page 174 Investigated Jumping Rate Models......Page 175 Empirical Results......Page 176 Conclusion......Page 177 References......Page 178 Introduction......Page 180 Differential Evolution Variants......Page 181 Multi-objective Optimization......Page 185 Promoting Diversity......Page 186 Performing Elitism......Page 187 Non-Pareto-Based Approaches......Page 189 Pareto-Based Approaches......Page 190 Combined Approaches......Page 195 Convergence Properties of Multi-Objective Differential Evolution......Page 196 Conclusions and Future Research Paths......Page 197 References......Page 199 Introduction......Page 204 The Workings of DE......Page 205 Implementation of Parallel Evolutionary Algorithms......Page 207 Single Objective Optimization......Page 208 Multiobjective Optimization......Page 212 Computing Simultaneously Local and Global Minima......Page 217 Exploration vs. Exploitation......Page 218 The Unsupervised $k$--Windows Clustering Algorithm......Page 219 The Proposed Clustering Operator......Page 220 Experimental Results on Multi-minima Discovery......Page 221 Neural Network Training Using DE......Page 223 Training Integer Weight Neural Networks with Threshold Activations......Page 224 Experiments on Neural Network Training......Page 225 Data Clustering......Page 226 Designing an Efficient Clustering Fitness Criterion......Page 228 Evolutionary Clustering under the WDF Objective Function......Page 229 Evolutionary Clustering Results......Page 230 Real Life Application: DNA Microarrays......Page 234 Algorithms and Methodology......Page 235 Presentation of Experiments in Evolutionary Dimension Reduction......Page 236 Genetic Programming......Page 237 Genetically Programmed Differential Evolution Mutation Operators......Page 239 Experimental Discovery of Genetically Programmed Operators......Page 240 Synopsis......Page 242 References......Page 243 Introduction......Page 246 The DE Method in Antenna Applications......Page 247 The DE Method in Radiofrequency and Microwave Imaging......Page 253 Conclusions......Page 259 References......Page 260 Introduction......Page 263 Problem Constraints......Page 265 Economic Dispatch Using Differential Evolution......Page 266 Computer Simulation......Page 268 Dynamic Economic Dispatch......Page 269 System Constraints......Page 270 DED Using Hybrid Differential Evolution......Page 271 Simulation Results......Page 273 System Constraints......Page 275 UC Using Mixed Integer Hybrid Differential Evolution......Page 276 Simulation Results......Page 278 References......Page 279 Introduction......Page 280 Formulation of Economic Dispatch Problem......Page 281 Differential Evolution......Page 283 Chaotic Local Search......Page 285 Simulation Results......Page 287 Conclusion and Future Research......Page 289 References......Page 290 Introduction......Page 292 Related Work......Page 293 AODE Algorithm for Tuning a Chess Program......Page 294 Opposition......Page 295 Selection......Page 296 Adaptive Mutation......Page 297 Experiments......Page 298 Conclusions......Page 302 References......Page 303 Introduction......Page 304 Case Study I......Page 306 Case Study III......Page 308 Solution Representation and Evaluation......Page 309 Differential Evolution......Page 310 Real-Valued EA......Page 311 Fully Informed Particle Swarm......Page 312 Parameter Settings and Test Conditions......Page 313 Results......Page 314 Description......Page 316 Experimental Setup......Page 317 Results......Page 318 Conclusions and Further Work......Page 320 References......Page 321 Introduction......Page 323 RLV Model, Control Law and Clearance Criterion......Page 325 Clearance Criterion......Page 326 Optimisation Based Worst Case Analysis......Page 327 Random Initialisation......Page 328 Crossover......Page 329 Hybrid DE......Page 330 Worst-Case Analysis Results......Page 332 Conclusions......Page 335 References......Page 336 back-matter......Page 338

differential Evolution Is Arguably One Of The Hottest Topics In Today's Computational Intelligence Research. This Book Seeks To Present A Comprehensive Study Of The State Of The Art In This Technology And Also Directions For Future Research.

the Fourteen Chapters Of This Book Have Been Written By Leading Experts In The Area. The First Seven Chapters Focus On Algorithm Design, While The Last Seven Describe Real-world Applications. Chapter 1 Introduces The Basic Differential Evolution (de) Algorithm And Presents A Broad Overview Of The Field. Chapter 2 Presents A New, Rotationally Invariant De Algorithm. The Role Of Self-adaptive Control Parameters In De Is Investigated In Chapter 3. Chapters 4 And 5 Address Constrained Optimization; The Former Develops Suitable Stopping Conditions For The De Run, And The Latter Presents An Improved De Algorithm For Problems With Very Small Feasible Regions. A Novel De Algorithm, Based On The Concept Of Opposite Points, Is The Topic Of Chapter 6. Chapter 7 Provides A Survey Of Multi-objective Differential Evolution Algorithms. A Review Of The Major Application Areas Of Differential Evolution Is Presented In Chapter 8. Chapter 9 Discusses The Application Of Differential Evolution In Two Important Areas Of Applied Electromagnetics. Chapters 10 And 11 Focus On Applications Of Hybrid De Algorithms To Problems In Power System Optimization. Chapter 12 Applies The De Algorithm To Computer Chess. The Use Of De To Solve A Problem In Bioprocess Engineering Is Discussed In Chapter 13. Chapter 14 Describes The Application Of Hybrid Differential Evolution To A Problem In Control Engineering.

Artists and creators in interactive art and interaction design have long been conducting research on human-machine interaction. Through artistic, conceptual, social and critical projects, they have shown how interactive digital processes are essential elements for their artistic creations. Resulting prototypes have often reached beyond the art arena into areas such as mobile computing, intelligent ambiances, intelligent architecture, fashionable technologies, ubiquitous computing and pervasive gaming. Many of the early artist-developed interactive technologies have influenced new design practices, products and services of today's media society. This book brings together key theoreticians and practitioners of this field. It shows how historically relevant the issues of interaction and interface design are, as they can be analyzed not only from an engineering point of view but from a social, artistic and conceptual, and even commercial angle as well