This paper presents a new approach for designing test sequences to be generated on–chip. The proposed technique is based on machine learning, and provides a way to generate effi...
Christophe Fagot, Patrick Girard, Christian Landra...
In case-based reasoning (CBR) a problem is solved by matching the problem description to a previously solved case, using the past solution in solving the new problem. A case-based...
Decentralized Markov decision processes are frequently used to model cooperative multi-agent systems. In this paper, we identify a subclass of general DEC-MDPs that features regul...
Most classification algorithms are "passive", in that they assign a class label to each instance based only on the description given, even if that description is incompl...
A fundamental open problem in computational learning theory is whether there is an attribute efficient learning algorithm for the concept class of decision lists (Rivest, 1987; Bl...