# Computational Complexity: Theory, Techniques, and Applications

## Book Description

Complex systems are systems that comprise many interacting parts with the ability to generate a new quality of collective behavior through self-organization, e.g. the spontaneous formation of temporal, spatial or functional structures. These systems are often characterized by extreme sensitivity to initial conditions as well as emergent behavior that are not readily predictable or even completely deterministic. The recognition that the collective behavior of the whole system cannot be simply inferred from an understanding of the behavior of the individual components has led to the development of numerous sophisticated new computational and modeling tools with applications to a wide range of scientific, engineering, and societal phenomena. Computational Complexity: Theory, Techniques and Applications presents a detailed and integrated view of the theoretical basis, computational methods, and state-of-the-art approaches to investigating and modeling of inherently difficult problems whose solution requires extensive resources approaching the practical limits of present-day computer systems. This comprehensive and authoritative reference examines key components of computational complexity, including cellular automata, graph theory, data mining, granular computing, soft computing, wavelets, and more.

### Table of Contents

Chapter 1. Additive Cellular Automata

Chapter 2. Agent Based Computational Economics

Chapter 3. Agent Based Modeling and Artificial Life

Chapter 4. Agent Based Modeling and Computer Languages

Chapter 5. Agent Based Modeling, Large Scale Simulations

Chapter 6. Agent Based Modeling, Mathematical Formalism for

Chapter 7. Agent Based Modeling and Simulation

Chapter 8. Agent Based Modeling and Simulation, Introduction to

Chapter 9. Aggregation Operators and Soft Computing

Chapter 10. Algorithmic Complexity and Cellular Automata

Chapter 11. AmorphousComputing

Chapter 12. Analog Computation

Chapter 13. ArtificialChemistry

Chapter 14. Artificial Intelligence in Modeling and Simulation

Chapter 15. Bacterial Computing

Chapter 16. Bayesian Games: Games with Incomplete Information

Chapter 17. Bayesian Statistics

Chapter 18. Bivariate (Two-dimensional) Wavelets

Chapter 19. Branching Processes

Chapter 20. Cellular Automata as Models of Parallel Computation

Chapter 21. Cellular Automata, Classification of

Chapter 22. Cellular Automata, Emergent Phenomena in

Chapter 23. Cellular Automata and Groups

Chapter 24. Cellular Automata in Hyperbolic Spaces

Chapter 25. Cellular Automata and Language Theory

Chapter 26. Cellular Automata with Memory

Chapter 27. Cellular Automata Modeling of Physical Systems

Chapter 28. Cellular Automata in Triangular, Pentagonal and Hexagonal Tessellations

Chapter 29. Cellular Automata, Universality of

Chapter 30. Cellular Automaton Modeling

Chapter 31. Cellular Computing

Chapter 32. Chaotic Behavior of Cellular Automata

Chapter 33. Community Structure in Graphs

Chapter 34. Comparison of Discrete and Continuous Wavelet Transforms

Chapter 35. Complex

Chapter 36. Complexity in Systems Level Biology and Genetics: Statistical Perspectives

Chapter 37. Complex Networks and Graph Theory

Chapter 38. Complex Networks, Visualization of

Chapter 39. Computer Graphics and Games, Agent Based Modeling in

Chapter 40. Computing in Geometrical Constrained Excitable Chemical Systems

Chapter 41. Computing with Solitons

Chapter 42. Cooperative Games

Chapter 43. Cooperative Games (Von NeumannÃ¢Â•ÂﬁMorgenstern Stable Sets)

Chapter 44. Cooperative Multi-hierarchical Query Answering Systems

Chapter 45. Correlated Equilibria and Communication in Games

Chapter 46. Correlations in Complex Systems

Chapter 47. Cost Sharing

Chapter 48. Curvelets and Ridgelets

Chapter 49. Data and Dimensionality Reduction in Data Analysis and System Modeling

Chapter 50. Data-Mining and Knowledge Discovery: Case-Based Reasoning, Nearest Neighbor and Rough Sets

Chapter 51. Data-Mining and Knowledge Discovery, Introduction to

Chapter 52. Data-Mining and Knowledge Discovery, Neural Networks in

Chapter 53. Decision Trees

Chapter 54. Dependency and Granularity inData

Chapter 55. Differential Games

Chapter 56. Discovery Systems

Chapter 57. DNA Computing

Chapter 58. Dynamic

Chapter 59. Dynamics of Cellular Automata in Non-compact Spaces

Chapter 60. Embodied and Situated Agents, Adaptive Behavior in

Chapter 61. Entropy

Chapter 62. Ergodic Theory of Cellular Automata

Chapter 63. Evolutionary Game Theory

Chapter 64. Evolution in Materio

Chapter 65. Evolving Cellular Automata

Chapter 66. Evolving Fuzzy Systems

Chapter 67. Extreme Value Statistics

Chapter 68. Fair Division *

Chapter 69. Field Theoretic Methods

Chapter 70. Firing Squad Synchronization Problem in Cellular Automata

Chapter 71. Fluctuations

Chapter 72. Food Webs

Chapter 73. Fuzzy Logic

Chapter 74. Fuzzy Logic, Type-2 and Uncertainty

Chapter 75. Fuzzy Optimization

Chapter 76. Fuzzy Probability Theory

Chapter 77. Fuzzy Sets Theory, Foundations of

Chapter 78. Fuzzy System Models

Chapter 79. Game Theory, Introduction to

Chapter 80. Game Theory and Strategic Complexity

Chapter 81. Genetic and Evolutionary Algorithms and Programming: General Introduction and Application to Game Playing

Chapter 82. Genetic-Fuzzy Data Mining Techniques

Chapter 83. Gliders in Cellular Automata

Chapter 84. Granular Computing and Data Mining for Ordered Data: The Dominance-Based Rough Set Approach

Chapter 85. Granular Computing, Information Models for

Chapter 86. Granular Computing, Introduction to

Chapter 87. Granular Computing and Modeling of the Uncertainty in Quantum Mechanics

Chapter 88. Granular Computing, Philosophical Foundation for

Chapter 89. Granular Computing: Practices, Theories, and Future Directions

Chapter 90. Granular Computing, Principles and Perspectives of

Chapter 91. Granular Computing System Vulnerabilities: Exploring the Dark Side of Social Networking Communities

Chapter 92. Granular Model for Data Mining

Chapter 93. Granular Neural Network

Chapter 94. Granulation of Knowledge: Similarity Based Approach in Information and Decision Systems

Chapter 95. Growth Models for Networks

Chapter 96. Growth Phenomena in Cellular Automata

Chapter 97. Hierarchical Dynamics

Chapter 98. Human Sexual Networks

Chapter 99. Hybrid Soft Computing Models for Systems Modeling and Control

Chapter 100. Identification of Cellular Automata

Chapter 101. Immunecomputing

Chapter 102. Implementation Theory

Chapter 103. Inspection Games

Chapter 104. Intelligent Control

Chapter 105. Intelligent Systems, Introduction to

Chapter 106. Interaction Based Computing in Physics

Chapter 107. Internet Topology

Chapter 108. Knowledge Discovery: Clustering

Chapter 109. Learning in Games

Chapter 110. Learning and Planning (Intelligent Systems)

Chapter 111. Levy Statistics and Anomalous Transport: Levy Flights and Subdiffusion

Chapter 112. Link Analysis and Web Search

Chapter 113. Logic and Geometry of Agents in Agent-Based Modeling

Chapter 114. Machine Learning, Ensemble Methods in

Chapter 115. Manipulating Data and Dimension Reduction Methods: Feature Selection

Chapter 116. Market Games and Clubs

Chapter 117. Mathematical Basis of Cellular Automata, Introduction to

Chapter 118. Mechanical Computing: The Computational Complexity of Physical Devices

Chapter 119. Mechanism Design

Chapter 120. Membrane Computing

Chapter 121. Minority Games

Chapter 122. Mobile Agents

Chapter 123. Molecular Automata

Chapter 124. Motifs

Chapter 125. Multi-Granular Computing and Quotient Structure

Chapter 126. Multivariate Splines and Their Applications

Chapter 127. Multiwavelets

Chapter 128. Nanocomputers

Chapter 129. Network Analysis, Longitudinal Methods of

Chapter 130. Networks and Stability

Chapter 131. Neuro-fuzzy Systems

Chapter 132. Non-negative Matrices and Digraphs

Chapter 133. Non-standard Analysis, an Invitation to

Chapter 134. Numerical Issues When Using Wavelets

Chapter 135. Optical Computing

Chapter 136. Phase Transitions in Cellular Automata

Chapter 137. Popular Wavelet Families and Filters and Their Use

Chapter 138. Positional Analysis and Blockmodeling

Chapter 139. Possibility Theory

Chapter 140. Principal-Agent Models

Chapter 141. Probability Densities in Complex Systems, Measuring

Chapter 142. Probability Distributions in Complex Systems

Chapter 143. Probability and Statistics in Complex Systems, Introduction to

Chapter 144. Quantum Algorithms

Chapter 145. Quantum Algorithms and Complexity for Continuous Problems

Chapter 146. Quantum Cellular Automata

Chapter 147. Quantum Computational Complexity

Chapter 148. Quantum Computing

Chapter 149. Quantum Computing with Trapped Ions

Chapter 150. Quantum Computing Using Optics

Chapter 151. Quantum Cryptography

Chapter 152. Quantum Error Correction and Fault Tolerant Quantum Computing

Chapter 153. Quantum Information Processing

Chapter 154. Quantum Information Science, Introduction to

Chapter 155. Random Graphs, a Whirlwind Tour of

Chapter 156. Random Matrix Theory

Chapter 157. Random Walks in Random Environment

Chapter 158. Rational, Goal-Oriented Agents

Chapter 159. Reaction-Diffusion Computing

Chapter 160. Record Statistics and Dynamics

Chapter 161. Repeated Games with Complete Information

Chapter 162. Repeated Games with Incomplete Information

Chapter 163. Reputation Effects

Chapter 164. Reversible Cellular Automata

Chapter 165. Reversible Computing

Chapter 166. Rough and Rough-Fuzzy Sets in Design of Information Systems

Chapter 167. Rough Set Data Analysis

Chapter 168. Rough Sets in Decision Making

Chapter 169. Rough Sets: Foundations and Perspectives

Chapter 170. Rule Induction, Missing Attribute Values and Discretization

Chapter 171. Self-organized Criticality and Cellular Automata

Chapter 172. Self-Replication and Cellular Automata

Chapter 173. Semantic Web

Chapter 174. Signaling Games

Chapter 175. Social Network Analysis, Estimation and Sampling in

Chapter 176. Social Network Analysis, Graph Theoretical Approaches to

Chapter 177. Social Network Analysis, Large-Scale

Chapter 178. Social Network Analysis, Overview of

Chapter 179. Social Network Analysis, Two-Mode Concepts in

Chapter 180. Social Networks, Algebraic Models for

Chapter 181. Social Networks, Diffusion Processes in

Chapter 182. Social Networks, Exponential Random Graph ( p * ) Models for

Chapter 183. Social Networks and Granular Computing

Chapter 184. Social Network Visualization, Methods of

Chapter 185. Social Phenomena Simulation

Chapter 186. Social Processes, Simulation Models of

Chapter 187. Soft Computing, Introduction to

Chapter 188. Static Games

Chapter 189. Statistical Applications of Wavelets

Chapter 190. Statistics with Imprecise Data

Chapter 191. Stochastic Games

Chapter 192. Stochastic Loewner Evolution: Linking Universality, Criticality and Conformal Invariance in Complex Systems

Chapter 193. Stochastic Processes

Chapter 194. Structurally Dynamic Cellular Automata

Chapter 195. Swarm Intelligence

Chapter 196. Synchronization Phenomena on Networks

Chapter 197. Thermodynamics of Computation

Chapter 198. Tiling Problem and Undecidability in Cellular Automata

Chapter 199. Topological Dynamics of Cellular Automata

Chapter 200. Two-Sided Matching Models

Chapter 201. Unconventional Computing, Introduction to

Chapter 202. Unconventional Computing, Novel Hardware for

Chapter 203. Voting

Chapter 204. Voting Procedures, Complexity of

Chapter 205. Wavelets, Introduction to

Chapter 206. Wavelets and the Lifting Scheme

Chapter 207. Wavelets and PDE Techniques in Image Processing, a Quick Tour of

Chapter 208. World Wide Web, Graph Structure

Chapter 209. Zero-Sum Two Person Games

## Book Details

- Title: Computational Complexity: Theory, Techniques, and Applications
- Author: Robert A. Meyers
- Length: 3536 pages
- Edition: 2012
- Language: English
- Publisher: Springer
- Publication Date: 2011-10-19
- ISBN-10: 1461417996
- ISBN-13: 9781461417996

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