Andreas L. Symeonidis – författare

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.

This monograph discusses software reuse and how it can be applied at different stages of the software development process, on different types of data and at different levels of granularity. Several challenging hypotheses are analyzed and confronted using novel data-driven methodologies, in order to solve problems in requirements elicitation and specification extraction, software design and implementation, as well as software quality assurance.

The book is accompanied by a number of tools, libraries and working prototypes in order to practically illustrate how the phases of the software engineering life cycle can benefit from unlocking the potential of data.

Software engineering researchers, experts, and practitioners can benefit from the various methodologies presented and can better understand how knowledge extracted from software data residing in various repositories can be combined and used to enable effective decision making and save considerable time and effortthrough software reuse. Mining Software Engineering Data for Software Reuse can also prove handy for graduate-level students in software engineering.

This book constitutes the thoroughly refereed and revised selected papers from the 10th International Workshop on Agents and Data Mining Interactions, ADMI 2014, held in Paris, France, in May 2014 as satellite workshop of AAMAS 2014, the 13th International Conference on Autonomous Agents and Multiagent Systems.

The 11 papers presented were carefully reviewed and selected from numerous submissions for inclusion in this volume. They present current research and engineering results, as well as potential challenges and prospects encountered in the respective communities and the coupling between agents and data mining.