We describe a general technique for expressing domain knowledge in constraint satisfaction problems, and using it to develop optimized parallel arc consistency algorithms for the ...
In this paper, we present QUALEX, a system and algorithm for generating first-order qualitative causal graphs for tutorial purposes based on de Kleer and Brown's qualitative ...
Recent results in the foundations of probability theory indicate that a conditional probability can be viewed as a probability attached to a mathematical entity called a measure-f...
AI and connectionist approaches to learning from examples differ in knowledge-base representation and inductive mechanisms. To explore these differences we experiment with a syste...
Incremental conceptual clustering is an important area of machine learning. It is concerned with summarizing data in a form of concept hierarchies, which will eventually ease the ...