Providing an overview of the use of unified computational intelligence in a complex environment, this text examines the topic in the context of economic, financial and social dynamics.
Providing an overview of the use of unified computational intelligence in a complex environment, this text examines the topic in the context of econom...
Recent work on the behavior of swarming creatures such as bees posits an innate collective intelligence that gives rise to myriad computational problem-solving techniques. This volume is both an introduction to the topic and a survey of leading-edge research.
Recent work on the behavior of swarming creatures such as bees posits an innate collective intelligence that gives rise to myriad computational proble...
A collection of studies covering the spectrum of computational intelligence applications with emphasis on their application to challenging real-world problems. It is suitable for researchers, practitioners and advanced-level students interested in the theory and practice of using computational intelligence in real-world applications.
A collection of studies covering the spectrum of computational intelligence applications with emphasis on their application to challenging real-world ...
Reinforcement learning encompasses both a science of adaptive behavior of rational beings in uncertain environments and a computational methodology for finding optimal behaviors for challenging problems in control, optimization and adaptive behavior of intelligent agents. As a field, reinforcement learning has progressed tremendously in the past decade.
The main goal of this book is to present an up-to-date series of survey articles on the main contemporary sub-fields of reinforcement learning. This includes surveys on partially observable environments, hierarchical task...
Reinforcement learning encompasses both a science of adaptive behavior of rational beings in uncertain environments and a computational methodology...
This book focuses on the different steps involved in the conception, implementation and application of Estimation of distribution algorithms (EDAs) that use Markov networks and undirected models in general.
This book focuses on the different steps involved in the conception, implementation and application of Estimation of distribution algorithms (EDAs) th...
Optimization is an integral part to science and engineering. Most real-world applications involve complex optimization processes, which are di?cult to solve without advanced computational tools. With the increasing challenges of ful?lling optimization goals of current applications there is a strong drive to advancethe developmentofe?cientoptimizers. The challengesintroduced by emerging problems include: objective functions which are prohibitively expensive to evaluate, so ty- callysoonlyasmallnumber ofobjectivefunctionevaluationscanbemade during the entire search, objective functions which...
Optimization is an integral part to science and engineering. Most real-world applications involve complex optimization processes, which are di?cult to...
This is the first book to present a computational intelligence architecture capable of learning in unsupervised, supervised, or reinforcement learning modes. It is also the first to cover applications of time scales mathematics to engineering applications.
This is the first book to present a computational intelligence architecture capable of learning in unsupervised, supervised, or reinforcement learning...
For many engineering problems we require optimization processes with dynamic adaptation as we aim to establish the dimension of the search space where the optimum solution resides and develop robust techniques to avoid the local optima usually associated with multimodal problems. This book explores multidimensional particle swarm optimization, a technique developed by the authors that addresses these requirements in a well-defined algorithmic approach.
After an introduction to the key optimization techniques, the authors introduce their unified framework and demonstrate its...
For many engineering problems we require optimization processes with dynamic adaptation as we aim to establish the dimension of the search space wh...
From nature, we observe swarming behavior in the form of ant colonies, bird flocking, animal herding, honey bees, swarming of bacteria, and many more. It is only in recent years that researchers have taken notice of such natural swarming systems as culmination of some form of innate collective intelligence, albeit swarm intelligence (SI) - a metaphor that inspires a myriad of computational problem-solving techniques. In computational intelligence, swarm-like algorithms have been successfully applied to solve many real-world problems in engineering and sciences. This handbook volume...
From nature, we observe swarming behavior in the form of ant colonies, bird flocking, animal herding, honey bees, swarming of bacteria, and many mo...
Reinforcement learning encompasses both a science of adaptive behavior of rational beings in uncertain environments and a computational methodology for finding optimal behaviors for challenging problems in control, optimization and adaptive behavior of intelligent agents. As a field, reinforcement learning has progressed tremendously in the past decade.
The main goal of this book is to present an up-to-date series of survey articles on the main contemporary sub-fields of reinforcement learning. This includes surveys on partially observable environments, hierarchical task...
Reinforcement learning encompasses both a science of adaptive behavior of rational beings in uncertain environments and a computational methodology...
