The field of biologically inspired computation has coexisted with mainstream computing since the 1930s, and the pioneers in this area include Warren McCulloch, Walter Pitts, Robert Rosen, Otto Schmitt, Alan Turing, John von Neumann and Norbert Wiener. Ideas arising out of studies of biology have permeated algorithmics, automata theory, artificial intelligence, graphics, information systems and software design. Within this context, the biomolecular, cellular and tissue levels of biological organisation have had a considerable inspirational impact on the development of computational ideas. Such...
The field of biologically inspired computation has coexisted with mainstream computing since the 1930s, and the pioneers in this area include Warren M...
Problems demanding globally optimal solutions are ubiquitous, yet many are intractable when they involve constrained functions having many local optima and interacting, mixed-type variables.
The differential evolution (DE) algorithm is a practical approach to global numerical optimization which is easy to understand, simple to implement, reliable, and fast. Packed with illustrations, computer code, new insights, and practical advice, this volume explores DE in both principle and practice. It is a valuable resource for professionals needing a proven optimizer and for students wanting...
Problems demanding globally optimal solutions are ubiquitous, yet many are intractable when they involve constrained functions having many local op...
The robust capability of evolutionary algorithms (EAs) to find solutions to difficult problems has permitted them to become popular as optimization and search techniques for many industries. Despite the success of EAs, the resultant solutions are often fragile and prone to failure when the problem changes, usually requiring human intervention to keep the EA on track. Since many optimization problems in engineering, finance, and information technology require systems that can adapt to changes over time, it is desirable that EAs be able to respond to changes in the environment on their own....
The robust capability of evolutionary algorithms (EAs) to find solutions to difficult problems has permitted them to become popular as optimization an...
Evolutionary algorithms (EAs) is now a mature problem-solving family of heuristics that has found its way into many important real-life problems and into leading-edge scientific research. Spatially structured EAs have different properties than standard, mixing EAs. By virtue of the structured disposition of the population members they bring about new dynamical features that can be harnessed to solve difficult problems faster and more efficiently. This book describes the state of the art in spatially structured EAs by using graph concepts as a unifying theme. The models, their analysis, and...
Evolutionary algorithms (EAs) is now a mature problem-solving family of heuristics that has found its way into many important real-life problems an...
Membrane computing is a branch of natural computing which investigates computing models abstracted from the structure and functioning of living cells and from their interactions in tissues or higher-order biological structures. The models considered, called membrane systems (P systems), are parallel, distributed computing models, processing multisets of symbols in cell-like compartmental architectures. In many applications membrane systems have considerable advantages - among these are their inherently discrete nature, parallelism, transparency, scalability and nondeterminism.
In...
Membrane computing is a branch of natural computing which investigates computing models abstracted from the structure and functioning of living cel...
Predicting the future for financial gain is a difficult, sometimes profitable activity. The focus of this book is the application of biologically inspired algorithms (BIAs) to financial modelling.
In a detailed introduction, the authors explain computer trading on financial markets and the difficulties faced in financial market modelling. Then Part I provides a thorough guide to the various bioinspired methodologies - neural networks, evolutionary computing (particularly genetic algorithms and grammatical evolution), particle swarm and ant colony optimization, and immune systems....
Predicting the future for financial gain is a difficult, sometimes profitable activity. The focus of this book is the application of biologically i...
Nanoscale science and computing is becoming a major research area as today's scientists try to understand the processes of natural and biomolecular computing. The field is concerned with the architectures and design of molecular self-assembly, nanostructures and molecular devices, and with understanding and exploiting the computational processes of biomolecules in nature.
This book offers a unique and authoritative perspective on current research in nanoscale science, engineering and computing. Leading researchers cover the topics of DNA self-assembly in two-dimensional arrays and...
Nanoscale science and computing is becoming a major research area as today's scientists try to understand the processes of natural and biomolecular...
This book introduces the new experimentalism in evolutionary computation, providing tools to understand algorithms and programs and their interaction with optimization problems. It develops and applies statistical techniques to analyze and compare modern search heuristics such as evolutionary algorithms and particle swarm optimization. The book bridges the gap between theory and experiment by providing a self-contained experimental methodology and many examples.
This book introduces the new experimentalism in evolutionary computation, providing tools to understand algorithms and programs and their interacti...
At the beginning of the 1990s research started in how to combine soft comput- ing with reconfigurable hardware in a quite unique way. One of the methods that was developed has been called evolvable hardware. Thanks to evolution- ary algorithms researchers have started to evolve electronic circuits routinely. A number of interesting circuits - with features unreachable by means of con- ventional techniques - have been developed. Evolvable hardware is quite pop- ular right now; more than fifty research groups are spread out over the world. Evolvable hardware has become a part of the curriculum...
At the beginning of the 1990s research started in how to combine soft comput- ing with reconfigurable hardware in a quite unique way. One of the metho...
This book provides a unified framework that describes how genetic learning can be used to design pattern recognition and learning systems. It examines how a search technique, the genetic algorithm, can be used for pattern classification mainly through approximating decision boundaries. Coverage also demonstrates the effectiveness of the genetic classifiers vis-a-vis several widely used classifiers, including neural networks.
This book provides a unified framework that describes how genetic learning can be used to design pattern recognition and learning systems. It exami...
