I ?rst met Jingqiao when he had just commenced his PhD research in evolutionary algorithms with Arthur Sanderson at Rensselaer. Jingqiao s goals then were the investigation and development of a novel class of se- adaptivedi?erentialevolutionalgorithms, later calledJADE. I had remarked to Jingqiao then that Arthur always appreciated strong theoretical foun- tions in his research, so Jingqiao s prior mathematically rigorous work in communications systems would be very useful experience. Later in 2007, whenJingqiaohadcompletedmostofthetheoreticalandinitialexperimental work on JADE, I invited him...
I ?rst met Jingqiao when he had just commenced his PhD research in evolutionary algorithms with Arthur Sanderson at Rensselaer. Jingqiao s goals then ...
Agent based evolutionary search is an emerging paradigm in computational int- ligence offering the potential to conceptualize and solve a variety of complex problems such as currency trading, production planning, disaster response m- agement, business process management etc. There has been a significant growth in the number of publications related to the development and applications of agent based systems in recent years which has prompted special issues of journals and dedicated sessions in premier conferences. The notion of an agent with its ability to sense, learn and act autonomously -...
Agent based evolutionary search is an emerging paradigm in computational int- ligence offering the potential to conceptualize and solve a variety of c...
One major branch of enhancing the performance of evolutionary algorithms is the exploitation of linkage learning. This title intends to capture the progress of linkage learning, by compiling a series of technical chapters to keep abreast of the developments and trends in the area of linkage.
One major branch of enhancing the performance of evolutionary algorithms is the exploitation of linkage learning. This title intends to capture the pr...
Differential evolution is a simple, yet very powerful, stochastic global optimizer. This book focuses on applications of differential evolution in electromagnetics, showcasing its effectiveness in solving synthesis and design problems in electromagnetics.
Differential evolution is a simple, yet very powerful, stochastic global optimizer. This book focuses on applications of differential evolution in ...
"Practical Applications of Evolutionary Computation to Financial Engineering" presents the state of the art techniques in Financial Engineering using recent results in Machine Learning and Evolutionary Computation. This book bridges the gap between academics in computer science and traders and explains the basic ideas of the proposed systems and the financial problems in ways that can be understood by readers without previous knowledge on either of the fields. To cement the ideas discussed in the book, software packages are offered that implement the systems described within.
The...
"Practical Applications of Evolutionary Computation to Financial Engineering" presents the state of the art techniques in Financial Engineering usi...
One major branch of enhancing the performance of evolutionary algorithms is the exploitation of linkage learning. This monograph aims to capture the recent progress of linkage learning, by compiling a series of focused technical chapters to keep abreast of the developments and trends in the area of linkage. In evolutionary algorithms, linkage models the relation between decision variables with the genetic linkage observed in biological systems, and linkage learning connects computational optimization methodologies and natural evolution mechanisms. Exploitation of linkage learning can...
One major branch of enhancing the performance of evolutionary algorithms is the exploitation of linkage learning. This monograph aims to capture th...
In recent years, ELM has emerged as a revolutionary technique of computational intelligence, and has attracted considerable attentions. An extreme learning machine (ELM) is a single layer feed-forward neural network alike learning system, whose connections from the input layer to the hidden layer are randomly generated, while the connections from the hidden layer to the output layer are learned through linear learning methods. The outstanding merits of extreme learning machine (ELM) are its fast learning speed, trivial human intervene and high scalability.
This book contains some...
In recent years, ELM has emerged as a revolutionary technique of computational intelligence, and has attracted considerable attentions. An extreme ...
This book describes how the principle of self-sufficiency can be applied to a reconfigurable modular robotic organism. It shows the design considerations for a novel REPLICATOR robotic platform, both hardware and software, featuring the behavioral characteristics of social insect colonies. Following a comprehensive overview of some of the bio-inspired techniques already available, and of the state-of-the-art in re-configurable modular robotic systems, the book presents a novel power management system with fault-tolerant energy sharing, as well as its implementation in the REPLICATOR...
This book describes how the principle of self-sufficiency can be applied to a reconfigurable modular robotic organism. It shows the design consider...
This carefully edited book takes a walk through recent advances in adaptation and hybridization in the Computational Intelligence (CI) domain. It consists of ten chapters that are divided into three parts. The first part illustrates background information and provides some theoretical foundation tackling the CI domain, the second part deals with the adaptation in CI algorithms, while the third part focuses on the hybridization in CI.
This book can serve as an ideal reference for researchers and students of computer science, electrical and civil engineering, economy, and natural...
This carefully edited book takes a walk through recent advances in adaptation and hybridization in the Computational Intelligence (CI) domain. It c...
The work presented in this book is a combination of theoretical advancements of big data analysis, cloud computing, and their potential applications in scientific computing. The theoretical advancements are supported with illustrative examples and its applications in handling real life problems. The applications are mostly undertaken from real life situations. The book discusses major issues pertaining to big data analysis using computational intelligence techniques and some issues of cloud computing. An elaborate bibliography is provided at the end of each chapter. The material in this book...
The work presented in this book is a combination of theoretical advancements of big data analysis, cloud computing, and their potential applications i...
