Über den Autor
Peter Stone received his Ph.D. in Political Science from the University of Rochester in 2000. He taught Political Science at Stanford University and held a Faculty Fellowship at Tulane University's Center for Ethics and Public Affairs before joining the Political Science Department at Trinity College Dublin in 2011. He works in contemporary political theory, with particular interest in theories of justice, democratic theory, rational choice theory, and the philosophy of social science. He is the author of The Luck of the Draw: The Role of Lotteries in Decision Making (Oxford University Press, 2011) and the editor of Lotteries in Public Life: A Reader (Imprint Academic, 2011). His interdisciplinary approach to the study of human affairs is reflected in his publication record, which includes articles in such leading journals as Comparative Education Review, the Journal of Political Philosophy, the Journal of Theoretical Politics, Political Theory, Rationality and Society, Social Science Information, Social Theory and Practice, and Theory and Decision. He currently serves Secretary of the Political Studies Association of Ireland (PSAI) and as co-convenor of the PSAI's Political Theory Specialist Group. He has been a member of the Bertrand Russell Society (BRS) for over 25 years and a member of its Board of Directors for over 15 years. He has held numerous Society offices, including Secretary and Vice President. He founded two of the Society's local chapters, is a former editor of the Bertrand Russell Society Quarterly, and has held numerous other Society positions. With Tim Madigan, he is the co-editor of Bertrand Russell: Public Intellectual (Tiger Bark Press, 2016), which recently won the 2017 BRS Book Award.
Robotics technology has recently advanced to the point of being widely accessible for relatively low-budget research, as well as for graduate, undergraduate, and even secondary and primary school education. This lecture provides an example of how to productively use a cutting-edge advanced robotics platform for education and research by providing a detailed case study with the Sony AIBO robot, a vision-based legged robot. The case study used for this lecture is the UT Austin Villa RoboCup Four-Legged Team. This lecture describes both the development process and the technical details of its end result. The main contributions of this lecture are (i) a roadmap for new classes and research groups interested in intelligent autonomous robotics who are starting from scratch with a new robot, and (ii) documentation of the algorithms behind our own approach on the AIBOs with the goal of making them accessible for use on other vision-based and/or legged robot platforms.