Manuela M. Veloso – författare

This research monograph describes the integration of analogical and case-based reasoning into general problem solving and planning as a method of speedup learning. The method, based on derivational analogy, has been fully implemented in PRODIGY/ANALOGY and proven in practice to be amenable to scaling up, both in terms of domain and problem complexity.In this work, the strategy-level learning process is cast for the first time as the automation of the complete cycle of construction, storing, retrieving, and flexibly reusing problem solving experience. The algorithms involved are presented in detail and numerous examples are given. Thus the book addresses researchers as well as practitioners.

This book includes the thoroughly refereed post-conference proceedings of the 17th Annual RoboCup International Symposium, held in Eindhoven, The Netherlands, in June 2013. The 20 revised papers presented together with 11 champion team papers, 3 best paper awards, 11 oral presentations, and 19 special track on open-source hard- and software papers were carefully reviewed and selected from 78 submissions. The papers present current research and educational activities within the fields of robotics and artificial intelligence with a special focus to robot hardware and software, perception and action, robotic cognition and learning, multi-robot systems, human-robot interaction, education and edutainment, and applications.