Knowledge, hidden in voluminous data repositories routinely created and maintained by today s applications, can be extracted by data mining. The next step is to transform this discovered knowledge into the inference mechanisms or simply the behavior of agents and multi-agent systems. Agent Intelligence Through Data Mining addresses this issue, as well as the arguable challenge of generating intelligence from data while transferring it to a separate, possibly autonomous, software entity. This book contains a methodology, tools and techniques, and several examples of agent-based applications developed with this approach. This volume focuses mainly on the use of data mining for smarter, more efficient agents.

Agent Intelligence Through Data Mining is designed for a professional audience of researchers and practitioners in industry. This book is also suitable for graduate-level students in computer science."

Information technologies have evolved to an enabling science for natural resource management and conservation, environmental engineering, scientific simulation and integrated assessment studies. Computing plays a significant role in every day practices of environmental engineers, natural scientists, economists, and social scientists. The complexity of natural phenomena requires interdisciplinary approaches, where computing science offers the infrastructure for environmental data collection and management, scientific simulations, decision support documentation and reporting.

Ecology, environmental engineering and natural resource management comprise an excellent real-world testbed for IT system demonstration, while raising new challenges for computer science. Complexity, uncertainty and scaling issues of natural systems form a demanding application domain for sensor networks and earth observation systems; modelling, simulation and scientific workflows, data management and reporting, decision support and intelligent systems, distributed computing environments, geographical information systems, heterogeneous systems integration, software engineering, accounting systems and control systems.

This books offers a collection of papers presented at the 4th International Symposium on Environmental Engineering, held in May 2009, in Thessaloniki, Greece. Recent success stories in ecoinformatics, promising ideas and new challenges are discussed among computer scientists, environmental engineers, economists and social scientists, demonstrating new paradigms for problem solving and decision making.

Information technologies have evolved to an enabling science for natural resource management and conservation, environmental engineering, scientific simulation and integrated assessment studies. Computing plays a significant role in every day practices of environmental engineers, natural scientists, economists, and social scientists. The complexity of natural phenomena requires interdisciplinary approaches, where computing science offers the infrastructure for environmental data collection and management, scientific simulations, decision support documentation and reporting.

Ecology, environmental engineering and natural resource management comprise an excellent real-world testbed for IT system demonstration, while raising new challenges for computer science. Complexity, uncertainty and scaling issues of natural systems form a demanding application domain for sensor networks and earth observation systems; modelling, simulation and scientific workflows, data management and reporting, decision support and intelligent systems, distributed computing environments, geographical information systems, heterogeneous systems integration, software engineering, accounting systems and control systems.

This books offers a collection of papers presented at the 4th International Symposium on Environmental Engineering, held in May 2009, in Thessaloniki, Greece. Recent success stories in ecoinformatics, promising ideas and new challenges are discussed among computer scientists, environmental engineers, economists and social scientists, demonstrating new paradigms for problem solving and decision making.

This book addresses the use of data mining for smarter, more efficient agents, as well as the challenge of generating intelligence from data while transferring it to a separate, possibly autonomous, software entity. Following a brief review of data mining and agent technology fields, the book presents a methodology for developing multi-agent systems, describes available open-source tools, and demonstrates the application of the methodology on three different cases.