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foreword by Michael Arbib "Hard to put down and necessary to know -- Arkin's book provides a comprehensive intellectual history of robots and a thorough compilation of robotic organizational paradigms from reflexes through social interaction." -- Chris Brown, Professor of Computer Science, University of Rochester This introduction to the principles, design, and practice of intelligent behavior-based autonomous robotic systems is the first true survey of this robotics field. The author presents the tools and techniques central to the development of this class of systems in a clear and thorough manner. Following a discussion of the relevant biological and psychological models of behavior, he covers the use of knowledge and learning in autonomous robots, behavior-based and hybrid robot architectures, modular perception, robot colonies, and future trends in robot intelligence. The text throughout refers to actual implemented robots and includes many pictures and descriptions of hardware, making it clear that these are not abstract simulations, but real machines capable of perception, cognition, and action.
Risk detection and cyber security play a vital role in the use and success of contemporary computing. By utilizing the latest technological advances, more effective prevention techniques can be developed to protect against cyber threats. Detecting and Mitigating Robotic Cyber Security Risks is an essential reference publication for the latest research on new methodologies and applications in the areas of robotic and digital security. Featuring extensive coverage on a broad range of topics, such as authentication techniques, cloud security, and mobile robotics, this book is ideally designed for students, researchers, scientists, and engineers seeking current research on methods, models, and implementations of optimized security in digital contexts.
An introduction to the science and practice of autonomous robots that reviews over 300 current systems and examines the underlying technology.
Intelligence takes many forms. This exciting study explores the novel insight, basedon well-established ethological principles, that animals, humans, and autonomous robots can all beanalyzed as multi-task autonomous control systems. Biological adaptive systems, the authors argue,can in fact provide a better understanding of intelligence and rationality than that provided bytraditional AI.In this technically sophisticated, clearly written investigation of robot-animalanalogies, McFarland and Bösser show that a bee's accuracy in navigating on a cloudy day and amoth's simple but effective hearing mechanisms have as much to teach us about intelligent behavioras human models. In defining intelligent behavior, what matters is the behavioral outcome, not thenature of the mechanism by which the outcome is achieved. Similarly, in designing robots capable ofintelligent behavior, what matters is the behavioral outcome.McFarland and Bösser address theproblem of how to assess the consequences of robot behavior in a way that is meaningful in terms ofthe robot's intended role, comparing animal and robot in relation to rational behavior, goalseeking, task accomplishment, learning, and other important theoretical issues.David McFarland isReader in Animal Behaviour at the University of Oxford. Thomas Bösser is Head of the Man MachineResearch Group at Westfälische Wilhelms Universität, in Münster, and a partner in the consultingfirm Advanced Concepts.
The NATO sponsored Advanced Study Institute 'The Biology and Tech nology of Intelligent Autonomous Agents' was an extraordinary event. For two weeks it brought together the leading proponents of the new behavior oriented approach to Artificial Intelligence in Castel Ivano near Trento. The goal of the meeting was to establish a solid scientific and technological foun dation for the field of intelligent autonomous agents with a bias towards the new methodologies and techniques that have recently been developed in Ar tificial Intelligence under the strong influence of biology. Major themes of the conference were: bottom-up AI research, artificial life, neural networks and techniques of emergent functionality. The meeting was such an extraordinary event because it not only featured very high quality lectures on autonomous agents and the various fields feeding it, but also robot laboratories which were set up by the MIT AI laboratory (with a lab led by Rodney Brooks) and the VUB AI laboratory (with labs led by Tim Smithers and Luc Steels). This way the participants could also gain practical experience and discuss in concreto what the difficulties and achievements were of different approaches. In fact, the meeting has been such a success that a follow up meeting is planned for September 1995 in Monte Verita (Switzerland). This meeting is organised by Rolf Pfeifer (University of Zurich).
Designing Autonomous Agents provides a summary and overview of the radically different architectures that have been developed over the past few years for organizing robots. These architectures have led to major breakthroughs that promise to revolutionize the study of autonomous agents and perhaps artificial intelligence in general.The new architectures emphasize more direct coupling of sensing to action, distributedness and decentralization, dynamic interaction with the environment, and intrinsic mechanisms to cope with limited resources and incomplete knowledge. The research discussed here encompasses such important ideas as emergent functionality, task-level decomposition, and reasoning methods such as analogical representations and visual operations that make the task of perception more realistic.Pattie Maes is Research Associate at the Artificial Intelligence Laboratory of the University of Brussels and Visiting Faculty Member at the Artificial Intelligence Laboratory at MIT.Contents: A Biological Perspective on Autonomous Agent Design, Randall D. Beer, Hillel J. Chiel, Leon S. Sterling. Elephants Don't Play Chess, Rodney A. Brooks. What Are Plans For? Philip E. Agre and David Chapman. Action and Planning in Embedded Agents, Leslie Pack Kaelbling and Stanley J. Rosenschein. Situated Agents Can Have Goals, Pattie Maes. Exploiting Analogical Representations, Luc Steels. Internalized Plans: A Representation for Action Resources, David W. Payton. Integrating Behavioral, Perceptual, and World Knowledge in Reactive Navigation, Ronald C. Arkin. Symbol Grounding via a Hybrid Architecture in an Autonomous Assembly System, Chris Malcolm and Tim Smithers. Animal Behavior as a Paradigm for Developing Robot Autonomy, Tracy L. Anderson and Max Donath.
Until the mid-1980s, AI researchers assumed that an intelligent system doing high-level reasoning was necessary for the coupling of perception and action. In this traditional model, cognition mediates between perception and plans of action. Realizing that this core AI, as it was known, was illusory, Rodney A. Brooks turned the field of AI on its head by introducing the behavior-based approach to robotics. The cornerstone of behavior-based robotics is the realization that the coupling of perception and action gives rise to all the power of intelligence and that cognition is only in the eye of an observer. Behavior-based robotics has been the basis of successful applications in entertainment, service industries, agriculture, mining, and the home. It has given rise to both autonomous mobile robots and more recent humanoid robots such as Brooks' Cog. This book represents Brooks' initial formulation of and contributions to the development of the behavior-based approach to robotics. It presents all of the key philosophical and technical ideas that put this "bottom-up" approach at the forefront of current research in not only AI but all of cognitive science.

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