Applied Evolutionary Algorithms in Java

Portada
Springer Science & Business Media, 2003 M04 30 - 219 páginas
Genetic algorithms provide a powerful range of methods for solving complex engineering search and optimization algorithms. Their power can also lead to difficulty for new researchers and students who wish to apply such evolution-based methods. "Applied Evolutionary Algorithms in Java" offers a practical, hands-on guide to applying such algorithms to engineering and scientific problems. The concepts are illustrated through clear examples, ranging from simple to more complex problems domains; all based on real-world industrial problems. Examples are taken from image processing, fuzzy-logic control systems, mobile robots, and telecommunication network optimization problems. The Java-based toolkit provides an easy-to-use and essential visual interface, with integrated graphing and analysis tools. Topics and features: *inclusion of a complete Java toolkit for exploring evolutionary algorithms *strong use of visualization techniques, to increase understanding *coverage of all major evolutionary algorithms in common usage *broad range of industrially based example applications *includes examples and an appendix based on fuzzy logic This book is intended for students, researchers, and professionals interested in using evolutionary algorithms in their work. No mathematics beyond basic algebra and Cartesian graphs methods are required, as the aim is to encourage applying the Java toolkit to develop the power of these techniques.
 

Comentarios de la gente - Escribir un comentario

No encontramos ningún comentario en los lugares habituales.

Contenido

Introduction to Evolutionary Computing
1
12 History of Evolutionary Computing
2
13 Obstacles to Evolutionary Computation
3
15 Problem Domains
4
152 Optimisation versus Robustness
6
154 Fuzzy Logic
7
155 Bayesian networks
9
156 Artificial Neural Networks
10
63 Speciation and Distributed EA Methods
103
632 Parallel Genetic Programming with Mobile Agents
104
635 EA Visualisation Methods
107
64 Advanced EA Techniques
108
641 Multiobjective Optimisation
109
644 Parameter Control
110
65 Artificial Life and Coevolutionary Algorithms
111
66 Summary
113

157 Feedforward Networks
11
16 Applications
12
161 Problems
13
17 EvolutionBased Search
14
173 Pascal and Fortran
15
176 ObjectOriented Design
16
18 Summary
17
Further Reading
18
Principles of Natural Evolution
19
212 Biological Genes
20
221 Transcription from DNA to RNA
21
224 No Lamarckianism
22
228 Evolvability
23
2210 Sexual Recombination
24
2213 Dynamics and Morphogenesis
25
Further Reading
26
Genetic Algorithms
27
33 GA Theory
30
331 Deception
31
34 GA Operators
32
342 Crossover
33
343 Multipoint Crossover
34
345 FitnessProportionate Selection
36
346 Disadvantages of FitnessProportionate Selection
37
348 Tournament Selection
38
349 Scaling Methods
39
36 Selecting GA Methods
40
362 Operator Choice
42
38 Summary
45
Further Reading
46
Genetic Programming
47
421 VariableLength and TreeBased Representations
49
424 Function Closure
50
427 Graph Structure Encoding
51
43 GP Operators
52
434 Controlling Genome Growth
53
44 Genetic Programming Implementation
54
45 Summary
55
Further Reading
56
Engineering Examples Using Genetic Algorithms
57
53 Basics of Image Processing
58
532 Lookup Tables
59
54 Java and Image Processing
60
541 Example Application VEGA
61
55 Spectrographic Chromosome representation
67
56 Results
68
57 Summary Evolved Image Processing
70
58 Mobile Robot Control
71
581 Artificial Intelligence and Mobile Robots
72
583 Static Worlds
73
584 Reactive and Bottomup Control
74
585 Advantages of Reactive Control
76
59 Behaviour Management
77
591 Behaviour Synthesis Architecture
78
592 Standard Control Methods PID
81
510 Evolutionary Methods
82
Natural Agents
83
511 Fuzzy Logic Control
84
5111 Fuzzy Control of Subsumption Architectures
87
513 Robot Simulator
89
5131 The Robot Control Architecture
90
5132 Related Work
93
5133 Results
94
514 Analysis
98
515 Summary Evolving Hybrid Systems
99
Future Directions in Evolutionary Computing
101
Further Reading
114
The Future of Evolutionary Computing
115
73 Future Directions in Evolutionary Computing
116
732 Biological Inspiration
117
734 Adaptive Encoding and Hierarchy
118
74 Conclusion
119
Bibliography
121
Appendix A
133
A2 CC++ based EA Software
134
A4 Java Reference Guides
136
Appendix B
137
B21 Vectors and Arraylists
147
B3 Application Design
148
An Evolutionary and Ecosystem Research Platform
149
B41 Introduction
150
B43 Key Classes
152
B44 Configuration
153
B45 Illustrative Example Systems
154
B47 An Ecosystem Simulation Based on Echo
155
B48 Coevolutionary Function Optimisation
156
B49 Telecommunications Research Using Eos
157
A Telecommunications Application
158
B5 Traveling Salesman Problem
159
B6 Genetic Programming
163
B61 Observations from Running GPsys on the Lawnmower Problem
164
Eos References
167
Fuzzy Logic Systems
169
C2 Fuzzy Set Theory
170
C21 Fuzzy Operators
171
C23 Fuzzy IF
172
C24 Fuzzy Associative Memories
173
C25 Fuzzy Control systems
174
C26 Defuzzification
175
C27 Fuzzy Applications
178
C31 Advantages of Fuzzy Systems
179
C4 Summary
180
Appendix D
181
Programming Language and RunTime Environment
182
Units of Measure
183
NetworkLocal Connections Versus Dynamically Loaded Clients
184
Why a ClientServer Architecture?
185
Network and Local Connection Issues
186
Communication via Events and Requests
187
Keeping the RP1 Protocol LanguageIndependent
188
The port and hostName Properties
189
Loading RsProperties Files as a Resource
190
The Server
191
The Scheduler
192
The FloorPlan
194
Building a Virtual Robot
196
Life Cycle of the Demonstration Clients
197
How ClnMain Extends RsClient and Implements RsRunnable
199
The RsRunnable Interface
200
Building RsRunnable and RsClient into ClnMain
201
DemoMain Implements RsRunnable But Does Not Extend RsClient
202
Uploading the Body Plan
204
Running the Event Loop
205
Physical Layout of ClientZero
207
RsBodyShape
209
RsWheelSystem
210
The Sensor Classes
212
RsBodyTargetSensor
213
Events and Requests
214
Index
216
Derechos de autor

Otras ediciones - Ver todas

Términos y frases comunes

Información bibliográfica