Timothy Sands

Stanford University; Columbia University; Naval Postgraduate School

Dr. Timothy Sands graduated from Columbia University, Stanford University, and the Naval Postgraduate School. He is an Interna-tional Scholar Laureate of the Golden Key International Honor Society, a Fellow of the Defense Advanced Research Projects Agency, panelist of the National Science Foundation Graduate Research Fellowship program, and an interviewer for undergradu-ate admissions at Stanford University. He has published prolifically in archival journals, conference proceedings, books, and book chapters, in addition to giving plenary, keynote, and invitational presentations. He holds one patent in spacecraft attitude control. He is currently the Associate Dean of the Naval Postgrad-uate School’s Graduate School of Engineering and Applied Science having previously served as a university chief academic officer, dean, and research center director.

2books edited

2chapters authored

Latest work with IntechOpen by Timothy Sands

Kirchhoff’s laws give a mathematical description of electromechanics. Similarly, translational motion mechanics obey Newton’s laws, while rotational motion mechanics comply with Euler’s moment equations, a set of three nonlinear, coupled differential equations. Nonlinearities complicate the mathematical treatment of the seemingly simple action of rotating, and these complications lead to a robust lineage of research culminating here with a text on the ability to make rigid bodies in rotation become self-aware, and even learn. This book is meant for basic scientifically inclined readers commencing with a first chapter on the basics of stochastic artificial intelligence to bridge readers to very advanced topics of deterministic artificial intelligence, espoused in the book with applications to both electromechanics (e.g. the forced van der Pol equation) and also motion mechanics (i.e. Euler’s moment equations). The reader will learn how to bestow self-awareness and express optimal learning methods for the self-aware object (e.g. robot) that require no tuning and no interaction with humans for autonomous operation. The topics learned from reading this text will prepare students and faculty to investigate interesting problems of mechanics. It is the fondest hope of the editor and authors that readers enjoy the book.

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