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Nigel P. Cook

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N.S.W.) International Symposium on Experimental Robotics 1999 Sydney, P.I. Corke, Peter I. Corke, James P. Trevelyan

This book presents the proceedings of the 6th International Symposium on Experimental Robotics held in Sydney in March 1999. The editors and contributors represent the leading robotics research efforts from around the world. Micro-machines, interplanetary exploration, minimally invasive surgery and emerging humanoid robots are among the most obvious attainments of leading robotics research teams reported in this volume. Less obvious but equally significant are the fundamental advances in robot map-building and methods of communication between humans and machines that are demonstrated through experimental results. This collection of papers will provide the reader with a concise report on the current achievements and future trends in robotics research across the world.

Pietro Traldi

This essential book for the practicing mass spectroscopist will appeal to a variety of biochemists, pharmaceutical scientists, forensic, clinical and life scientists and analytical chemists.

Katsunari Okamoto

Fundamentals of Optical Waveguides is an essential resource for any researcher, professional or student involved in optics and communications engineering. Any reader interested in designing or actively working with optical devices must have a firm grasp of the principles of lightwave propagation. Katsunari Okamoto has presented this difficult technology clearly and concisely with several illustrations and equations. Optical theory encompassed in this reference includes coupled mode theory, nonlinear optical effects, finite element method, beam propagation method, staircase concatenation method, along with several central theorems and formulas. Since the publication of the well-received first edition of this book, planar lightwave circuits and photonic crystal fibers have fully matured. With this second edition the advances of these fibers along with other improvements on existing optical technologies are completely detailed. This comprehensive volume enables readers to...

Michael Mortenson

Describes and compares all the important mathematical methods for modeling curves, surfaces, and solids. Prepares the reader for more advanced topics, such as 3D modeling, CAD/CAM, animation, and scientific visualization. Incorporates references throughout the text to direct the reader to more specialized treatments of the subjects. Carefully designed illustrations and exercises support each mathematical concept presented. Offers hundreds of exercises to test the readers comprehension.

Jon Kleinberg, A‰va Tardos

Algorithm Design introduces algorithms by looking at the real-world problems that motivate them. The book teachesA a range of design and analysis techniques for problems that arise in computing applications. The text encourages an understanding of the algorithm design process and an appreciation of the role of algorithms in the broader field of computer science.

Jerry Banks, John Carson, Barry L. Nelson, David Nicol

This book provides a basic treatment of discrete-event simulation, including the proper collection and analysis of data, the use of analytic techniques, verification and validation of models, and designing simulation experiments. Contains up-to-date treatment of simulation of manufacturing and material handling systems. Includes numerous solved examples. Offers an integrated website. Explains how to interpret simulation software output. For those interested in learning more about discrete-event simulation.

Max O. Hallman

TRAVERSING PHILOSOPHICAL BOUNDARIES is the most comprehensive multicultural text/reader for introductory philosophy. Addressing six primary philosophical concerns?the self, reality, epistemology, ethics, politics, and religion?this book contains not only many readings from the Western canon, but also essential readings from many cultural perspectives not typically included in introductory philosophy classes. Asian, African, African-American, Latin American, and Feminist traditions are broadly represented and fully integrated into the exploration of these fundamental matters.

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High Quality Content by WIKIPEDIA articles! Inspired by related psychological theory, in computer science, reinforcement learning is a sub-area of machine learning concerned with how an agent ought to take actions in an environment so as to maximize some notion of long-term reward. Reinforcement learning algorithms attempt to find a policy that maps states of the world to the actions the agent ought to take in those states. In economics and game theory, reinforcement learning is considered as a boundedly rational interpretation of how equilibrium may arise. The environment is typically formulated as a finite-state Markov decision process (MDP), and reinforcement learning algorithms for this context are highly related to dynamic programming techniques. State transition probabilities and reward probabilities in the MDP are typically stochastic but stationary over the course of the problem.