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It has been recognized since the inception of Artificial Intelligence (AI) that abstractions, problem reformulations, and approximations (AR&A) are central to human common sense reasoning and problem solving and to the ability of systems to reason effectively in complex domains. AR&A techniques have been used to solve a variety of tasks, including automatic programming, constraint satisfaction, design, diagnosis, machine learning, search, planning, reasoning, game playing, scheduling, and theorem proving. The primary purpose of AR&A techniques in such settings is to overcome computational intractability. In addition, AR&A techniques are useful for accelerating learning and for summarizing se...
This book is a printed edition of the Special Issue "Plant Genetics and Biotechnology in Biodiversity" that was published in Diversity
This book constitutes the seventh official archival publication devoted to RoboCup. It documents the achievements presented at the 7th Robot World Cup Soccer and Rescue Competition and Conferences held in Padua, Italy, in July 2003. The 39 revised full papers and 35 revised poster papers presented together with an overview and roadmap for the RoboCup initiative and 3 invited papers were carefully reviewed and selected from 125 symposium paper submissions. This book is mandatory reading for the rapidly growing RoboCup community as well as a valuable source of reference and inspiration for R&D professionals interested in robotics, distributed artificial intelligence, and multi-agent systems.
This book presents the latest in mammary gland transgenesis, the exploitation of transgenic technology for the production of therapeutic proteins by routine or conventional methods. Following a section with an overview of all relevant methodologies, readers will find relevant information on the regulation of milk gene expression and bioreactor species such as cattle, rabbits and pigs.
ThesearetheproceedingsoftheRoboCup2004Symposium,heldattheInstituto Superior T ́ ecnico, in Lisbon, Portugal in conjunction with the RoboCup c- petition. The papers presented here document the many innovations in robotics that result from RoboCup. A problem in any branch of science or engineering is how to devise tests that can provide objective comparisons between alt- native methods. In recent years, competitive engineering challenges have been established to motivate researchers to tackle di?cult problems while providing a framework for the comparison of results. RoboCup was one of the ?rst such competitions and has been a model for the organization of challenges foll- ing sound scienti?c...
This book constitutes the refereed proceedings of the 2nd International Joint Conference of the 10th Ibero-American Conference on Artificial Intelligence, IBERAMIA 2006, and the 18th Brazilian Artificial Intelligence Symposium, SBIA 2006. The book presents 62 revised full papers together with 4 invited lectures. Topical sections include AI in education and intelligent tutoring systems, autonomous agents and multiagent systems, computer vision and pattern recognition, evolutionary computation and artificial life, and more.
The leading edge of computer science research is notoriously ?ckle. New trends come and go with alarming and unfailing regularity. In such a rapidly changing ?eld, the fact that research interest in a subject lasts more than a year is worthy of note. The fact that, after ?ve years, interest not only remains, but actually continues to grow is highly unusual. As 1998 marked the ?fth birthday of the International Workshop on Agent Theories, Architectures, and Languages (ATAL), it seemed appropriate for the organizers of the original workshop to comment on this remarkable growth, and re ect on how the ?eld has developed and matured. The ?rst ATAL workshop was co-located with the Eleventh Europea...
Multistrategy learning is one of the newest and most promising research directions in the development of machine learning systems. The objectives of research in this area are to study trade-offs between different learning strategies and to develop learning systems that employ multiple types of inference or computational paradigms in a learning process. Multistrategy systems offer significant advantages over monostrategy systems. They are more flexible in the type of input they can learn from and the type of knowledge they can acquire. As a consequence, multistrategy systems have the potential to be applicable to a wide range of practical problems. This volume is the first book in this fast growing field. It contains a selection of contributions by leading researchers specializing in this area. See below for earlier volumes in the series.
This book is a history of artificial intelligence, that audacious effort to duplicate in an artifact what we consider to be our most important property—our intelligence. It is an invitation for anybody with an interest in the future of the human race to participate in the inquiry.