Continuous Measurements and Quantitative Constraints: Challenge Problems for Discrete Modeling Techniques

Many techniques in artificial intelligence operate on discrete models, wherein each variable of a system description may take on only a finite number of discrete values. These discrete models are easy to acquire, they have computational advantages, and there are many well-developed algorithms for manipulating them. In contrast, the world presents us with many continuous processes we would like to simulate, identify or control. Many discrete techniques from AI are regularly applied to discrete abstractions of continuous processes. This of course is not always possible. It’s therefore important to consider whether one’s continuous problem lends itself to being