In many machine learning problems, labeled training data is limited but unlabeled data is ample. Some of these problems have instances that can be factored into multiple views, ea...
Both explanation-based and inductive learning techniques have proven successful in a variety of distributed domains. However, learning in multi-agent systems does not necessarily ...
While it is commonly agreed that analogy is useful in human problem solving, exactly how analogy can and should be used remains an intriguing problem. VanLehn (1998) for instance ...
The research concerning Java’s semantics and proof theory has mainly focussed on various aspects of sequential sub-languages. Java, however, integrates features of a class-based ...
— Developing a problem-domain independent methodology to automatically generate high performing solving strategies for specific problems is one of the challenging trends on hype...