F. Zhao and C. Bailey-Kellogg, "Intelligent simulation", AAAI Tutorial Forum, 1998. [preprint]

Intelligent simulation is a new problem-solving paradigm for data interpretation and control tasks in science and engineering. Because of rapid advances in information processing and microelectronics, many practical applications require real-time interpretation of information in order to effectively interact with the environment. The information is often in a data-rich form such as images, videos, or spatially distributed measurements of physical processes. For example, a network of computational agents embedded in a "smart building" must stitch together local measurements in order to ensure occupant comfort while minimizing energy consumption.

This tutorial introduces a body of computational theories, techniques, and languages collectively called intelligent simulation. We will develop imagistic reasoning techniques for finding structures in large scientific and engineering data sets and the spatial aggregation (SA) language for rapid prototyping of imagistic problem solvers. SA draws upon the experience gained in developing applications in a number of challenging domains such as data analysis and visualization (KAM), control (MAPS), and mechanical design (HIPAIR); it incorporates techniques from computer vision, qualitative reasoning, scientific computing, and computational geometry. We will demonstrate how new applications can be prototyped with the SA language, using case studies including weather data interpretation, fluid simulation, and nonlinear maglev control design. No previous knowledge of intelligent simulation is required.