Recent 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 and concept formulation.
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.
- Machine learning, when applied to robotics, is situated: it is embedded into a real-world system that tightly integrates perception, decision making and execution.
- Since robot learning involves decision making, there is an inherent active learning issue.
- Robotic domains are usually complex, yet the expense of using actual robotic hardware often prohibits the collection of large amounts of training data.
- Most robotic systems are real-time systems. Decisions must be made within critical or practical time constraints.
These characteristics present challenges and constraints to the learning system. Since these characteristics are shared by other important real-world application domains, robotics is a highly attractive area for research on machine learning.
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).
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The spoken language is the most important means of human information transmission. Thus, as we enter the age of the Information Society
, the use of the man-machine interface through the spoken language becomes increasingly important. Due to the extent of the problems involved, however, full realization of such an interface calls for coordination of research efforts
beyond the scope of a single group or institution.
Thus a nationwide research project was conceived and started in 1987 as one of the first Priority Research Areas supported by the Ministry of Education, Science and Culture of Japan. The
project was carried out in collaboration with over 190 researchers in Japan.
The present volume begins with an overview of the project, followed by 41 papers presented at the symposia. This work is expected to serve as an important source of information on each of the nine topics adopted for intensive study under the project.
This book will serve as a guideline for further work in the important scientific and technological field of spoken language processing.
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