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The purpose of our research is to enhance the efficiency of AI problem solvers by automating representation changes. We have developed a system that improves the description of input problems and selects an appropriate search algorithm for each given problem. Motivation. Researchers have accumulated much evidence on the impor tance of appropriate representations for the efficiency of AI systems. The same problem may be easy or difficult, depending on the way we describe it and on the search algorithm we use. Previous work on the automatic im provement of problem descriptions has mostly been limited to the design of individual learning algorithms. The user has traditionally been responsible f...
Artificial Intelligence is one of the most fascinating and unusual areas of academic study to have emerged this century. For some, AI is a true scientific discipline, that has made important and fundamental contributions to the use of computation for our understanding of nature and phenomena of the human mind; for others, AI is the black art of computer science. Artificial Intelligence Today provides a showcase for the field of AI as it stands today. The editors invited contributions both from traditional subfields of AI, such as theorem proving, as well as from subfields that have emerged more recently, such as agents, AI and the Internet, or synthetic actors. The papers themselves are a mixture of more specialized research papers and authorative survey papers. The secondary purpose of this book is to celebrate Springer-Verlag's Lecture Notes in Artificial Intelligence series.
Contributes tools and techniques to create physical multiagent systems (MAS) in domains where each agent has insufficient capabilities for solving the problem alone. This book's contibutions address the problem of league-independent solutions and provide means to create more generally applicable approaches.
A celebration of the women who furthered computer technology, from the nineteenth century to the present day.
An agent is a system capable of perceiving the environment, reasoning with the percepts and then acting upon the world. Agents can be purely software systems, in which case their percepts and output `actions' are encoded binary strings. However, agents can also be realized in hardware, and then they are robots. The Artificial Intelligence community frequently views robots as embodied intelligent agents. The First International Conference on Autonomous Agents was held in Santa Monica, California, in February 1997. This conference brought together researchers from around the world with interests in agents, whether implemented purely in software or in hardware. The conference featured such topics as intelligent software agents, agents in virtual environments, agents in the entertainment industry, and robotic agents. Papers on robotic agents were selected for this volume. Autonomous Agents will be of interest to researchers and students in the area of artificial intelligence and robotics.
Learning from Demonstration (LfD) explores techniques for learning a task policy from examples provided by a human teacher. The field of LfD has grown into an extensive body of literature over the past 30 years, with a wide variety of approaches for encoding human demonstrations and modeling skills and tasks. Additionally, we have recently seen a focus on gathering data from non-expert human teachers (i.e., domain experts but not robotics experts). In this book, we provide an introduction to the field with a focus on the unique technical challenges associated with designing robots that learn from naive human teachers. We begin, in the introduction, with a unification of the various terminolo...
RoboCup 2002, the 6th Robot World Cup Soccer and Rescue Competitions and Conference, took place during June 19–25, 2002, at the Fukuoka Dome (main venue) in Fukuoka, Japan. It was, by far, the RoboCup event with the largestnumberofregisteredparticipants(1004persons,distributedin188teams from 29 countries) and visitors (around 120,000 persons). As was done in its previous editions since 1997, the event included several robotic competitions and aninternationalsymposium.Thepapersandposterspresentedatthesymposium constitutethemainpartofthisbook.Leaguereportsinthe?nalsectiondescribe signi?cant advances in each league and the results. The symposium organizers received 76 submissions, among which...
This proceedings volume documents recent cutting-edge developments in multi-robot systems research. This volume is the result of the Third International workshop on Multi-Robot Systems that was held in March 2005 at the Naval Research Laboratory in Washington, D.C. This workshop brought together top researchers working in areas relevant to designing teams of autonomous vehicles, including robots and unmanned ground, air, surface, and undersea vehicles. The workshop focused on the challenging issues of team architectures, vehicle learning and adaptation, heterogeneous group control and cooperation, task selection, dynamic autonomy, mixed initiative, and human and robot team interaction. A broad range of applications of this technology are presented in this volume, including UCAVS (Unmanned Combat Air Vehicles), micro-air vehicles, UUVs (Unmanned Underwater Vehicles), UGVs (Unmanned Ground vehicles), planetary exploration, assembly in space, clean-up, and urban search and rescue. This proceedings volume represents the contributions of the top researchers in this field and serves as a valuable tool for professionals in this interdisciplinary field.