Knowledge, hidden in voluminous data repositories routinely created and maintained by todaya (TM)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 book was first published in 2006. Technologists have the ideas. Lawyers know the rules. But for business managers and investors, rules and ideas don't readily combine into a strategic vision. No longer is intellectual property (IP) just a necessary expense for large technology companies. Competing and succeeding in the marketplace requires an in-depth understanding of IP - its use as a weapon, as a shield, and as a monetizable asset. Yet in a world where fortunes can rise or founder on the strength of an IP portfolio, hesitation to enter this arcane, unfamiliar world still abounds. This book equips the business manager with a working, practical knowledge essential to creating and exploiting IP wealth. It shows investors how to evaluate IP strength and competitive value. With its results-oriented perspective and international focus, Intellectual Property for Managers and Investors is essential for those with decision making-responsibility at the interface where business and innovation meet.
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