Evolutionary computing paradigms offer robust and powerful adaptive search mechanisms for system design. This book's thirteen chapters cover a wide area of topics in evolutionary computing and applications, including an introduction to evolutionary computing in system design; evolutionary neuro-fuzzy systems; and evolution of fuzzy controllers. The book will be useful to researchers in intelligent systems with interest in evolutionary computing, as well as application engineers and system designers.

This book covers multifaceted aspects of sustainable energy solutions for remote areas in the tropics, particularly focusing on Southeast Asia. With insights from both the academic world and real-life implementation, readers will gain an overview of the range of energy problems currently facing the remote tropics, and what potential solutions are available. The book provides a detailed overview of various energy needs in the Southeast Asian tropics, a region where a significant portion of the population still lives without access to electricity. It not only addresses technical solutions to the energy problems but also tackles the social and wider implications, offering readers a more holistic understanding of the potential held by renewable energy. The chapters are structured to present first an overview of the problem at hand, and then a description of the technologies that could potentially solve it. Applications of the technologies; business models that are now available or being developed; the impact of the technologies; and future, more sustainable solutions are all discussed. Given its in-depth analysis, the book will be of interest to energy professionals in the tropics, energy policymakers, and students studying sustainable energy.

In today's world, the increasing requirement for emulating the behavior of real-world applications for achieving effective management and control has necessitated the usage of advanced computational techniques. Computational intelligence-based techniques that combine a variety of problem solvers are becoming increasingly pervasive. The ability of these methods to adapt to the dynamically changing environment and learn in an online manner has increased their usefulness in simulating intelligent behaviors as observed in humans. These intelligent systems are able to handle the stochastic and uncertain nature of the real-world problems. Application domains requiring interaction of people or organizations with different, even possibly conflicting goals and proprietary information handling are growing exponentially. To efficiently handle these types of complex interactions, distributed problem solving systems like multiagent systems have become a necessity. The rapid advancements in network communication technologies have provided the platform for successful implementation of such intelligent agent-based problem solvers. An agent can be viewed as a self-contained, concurrently executing thread of control that encapsulates some state and communicates with its environment, and possibly other agents via message passing. Agent-based systems offer advantages when independently developed components must interoperate in a heterogenous environment. Such agent-based systems are increasingly being applied in a wide range of areas including telecommunications, Business process modeling, computer games, distributed system control and robot systems.

In today's world, the increasing requirement for emulating the behavior of real-world applications for achieving effective management and control has necessitated the usage of advanced computational techniques. Computational intelligence-based techniques that combine a variety of problem solvers are becoming increasingly pervasive. The ability of these methods to adapt to the dynamically changing environment and learn in an online manner has increased their usefulness in simulating intelligent behaviors as observed in humans. These intelligent systems are able to handle the stochastic and uncertain nature of the real-world problems. Application domains requiring interaction of people or organizations with different, even possibly conflicting goals and proprietary information handling are growing exponentially. To efficiently handle these types of complex interactions, distributed problem solving systems like multiagent systems have become a necessity. The rapid advancements in network communication technologies have provided the platform for successful implementation of such intelligent agent-based problem solvers. An agent can be viewed as a self-contained, concurrently executing thread of control that encapsulates some state and communicates with its environment, and possibly other agents via message passing. Agent-based systems offer advantages when independently developed components must interoperate in a heterogenous environment. Such agent-based systems are increasingly being applied in a wide range of areas including telecommunications, Business process modeling, computer games, distributed system control and robot systems.

Evolutionary computing paradigms offer robust and powerful adaptive search mechanisms for system design. This book includes thirteen chapters covering a wide area of topics in evolutionary computing and applications including: Introduction to evolutionary computing in system design; evolutionary neuro-fuzzy systems; evolution of fuzzy controllers; genetic algorithms for multi-classifier design; evolutionary grooming of traffic; evolutionary particle swarms; fuzzy logic systems using genetic algorithms; evolutionary algorithms and immune learning for neural network-based controller design; distributed problem solving using evolutionary learning; evolutionary computing within grid environment; evolutionary game theory in wireless mesh networks; hybrid multiobjective evolutionary algorithms for the sailor assignment problem; evolutionary techniques in hardware optimization. This book will be useful to researchers in intelligent systems with interest in evolutionary computing, application engineers and system designers. The book can also be used by students and lecturers as an advanced reading material for courses on evolutionary computing.

This book covers multifaceted aspects of sustainable energy solutions for remote areas in the tropics, particularly focusing on Southeast Asia. With insights from both the academic world and real-life implementation, readers will gain an overview of the range of energy problems currently facing the remote tropics, and what potential solutions are available. The book provides a detailed overview of various energy needs in the Southeast Asian tropics, a region where a significant portion of the population still lives without access to electricity. It not only addresses technical solutions to the energy problems but also tackles the social and wider implications, offering readers a more holistic understanding of the potential held by renewable energy. The chapters are structured to present first an overview of the problem at hand, and then a description of the technologies that could potentially solve it. Applications of the technologies; business models that are now available or being developed; the impact of the technologies; and future, more sustainable solutions are all discussed. Given its in-depth analysis, the book will be of interest to energy professionals in the tropics, energy policymakers, and students studying sustainable energy.