Mitchell, T.M.



Learning Problem-Solving Heuristics by Experimentation

Classics

Machine Learning: An Artificial Intelligence Approach contains tutorial overviews and research papers representative of trends in the area of machine learning as viewed from an artificial intelligence perspective. Part II covers important issues affecting the design of learning programs particularly programs that learn from examples. It also describes inductive learning systems. This book is intended for researchers in artificial intelligence, computer science, and cognitive psychology; students in artificial intelligence and related disciplines; and a diverse range of readers, including computer scientists, robotics experts, knowledge engineers, educators, philosophers, data analysts, psychologists, and electronic engineers."


Becoming increasingly reactive mobile robots

Classics

"We describe a robot control architecture which combines a stimulus-response subsystem for rapid reaction, with a search-based planner for handling unanticipated situations. The robot agent continually chooses which action it is to perform, using the stimulusresponse subsystem when possible, and falling back on the planning subsystem when necessary. Whenever it is forced to plan, it applies an explanation-based learning mechanism to formulate a new stimulus-response rule to cover this new situation and others similar to it. With experience, the agent becomes increasingly reactive as its learning component acquires new stimulus-response rules that eliminate the need for planning in similar subsequent situations. This Theo-Agent architecture is described, and results are presented demonstrating its ability to reduce routine reaction time for a simple mobile robot from minutes to under a second."In AAAI-90, Vol. 2, pp. 1051– 1058


Models of learning systems

Classics

Data base Adaptive Concept Management control formation systems systems systems alter alter alter assertions parameters structures Figure 1. A "learning system" is an adaptive system that responds acceptably within some time interval following a change in its environment, and a "self-repairing system" is one that responds acceptably within some time interval following a change in its internal structure. This approach was designed to utilize the existing arsenal of control techniques requiring exact specification of the plant. Two broad techniques exist for establishment of convergent control parameter adaptation schemes: search methods and stability analysis.


Models of learning systems

Classics

"The terms adaptation, learning, concept-formation, induction, self-organization, and self-repair have all been used in the context of learning system (LS) research. The research has been conducted within many different scientific communities, however, and these terms have come to have a variety of meanings. It is therefore often difficult to recognize that problems which are described differently may in fact be identical. Learning system models as well are often tuned to the require- ments of a particular discipline and are not suitable for application in related disciplines."In Encyclopedia of Computer Science and Technology, Vol. 11. Dekker