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Recent Advances in Robot LearningJudy A. Franklin, Tom M. Mitchell, and Sebastian ThrunRecent Advances in Robot Learning contains seven papers on robot learning written by leading researchers in the field. As the selection of papers illustrates, the field of robot learning is both active and diverse. A variety of machine learning methods, ranging from inductive logic programming to reinforcement learning, is being applied to many subproblems in robot perception and control, often with objectives as diverse as parameter calibration or concept formation. While no unified robot learning framework has yet emerged to cover the variety of problems and approaches described in these papers and other publications, a clear set of shared issues underlies many robot learning problems.
On the other hand, machine learning is also highly attractive to robotics. There is a great variety of open problems in robotics that defy a static, hand-coded solution. Recent Advances in Robot Learning is an edited volume of peer-reviewed original research comprising seven invited contributions by leading researchers. This research work has also been published as a special issue of Machine Learning (Volume 23, Numbers 2 and 3).
@BOOK{Franklin96a, EDITOR = {J. Franklin, T. Mitchell and S. Thrun}, YEAR = {1996}, TITLE = {Recent Advances in Robot Learning}, PUBLISHER = {Kluwer Academic Publishers}, ADDRESS = {Boston, MA} } |