This interdisciplinary approach to computer modeling addresses both traditional simulationists seeking the greater representational flexibility and ease of use that AI techniques offer, and computer scientists seeking the greater power and realism that rigorous simulation techniques can provide. First section reveals the theoretical underpinnings of AI and simulation. Second section describes application of simulation techniques to current problems in AI research. Third section discusses application of AI methods to simulation.

This volume contains papers in the areas of artificial intelligence, expert systems, symbolic computing and applications to scientific computing. Together, they provide an excellent overview of the dynamic state of these closely related fields. They reveal a future where scientific computation will increasingly involve symbolic and artificial intelligence tools as these software systems become more sophisticated; also a future where systems of computational science and engineering will be problem solving environments created with components from numerical analysis, computational geometry, symbolic computing and artificial intelligence.

Qualitative models are better able than traditional models to express states of incomplete knowledge about continuous mechanisms. Qualitative simulation guarantees to find all possible behaviors consistent with the knowledge in the model. This expressive power and coverage is important in problem solving for diagnosis, design, monitoring, explanation, and other applications of artificial intelligence.

Computational mechanics is a scientific discipline that marries physics, computers, and mathematics to emulate natural physical phenomena. It is a technology that allows scientists to study and predict the performance of various productsâ€"important for research and development in the industrialized world. This book describes current trends and future research directions in computational mechanics in areas where gaps exist in current knowledge and where major advances are crucial to continued technological developments in the United States.

I have long had an interest in the life sciences, but have had few opportunities to indulge that interest in my professional activities. It has only been through simulation that those opportunities have arisen. Some of my most enjoyable classes were those I taught to students in the life sciences, where I attempted to show them the value of simulation to their discipline. That there is such a value cannot be questioned. Whether you are interested in population ecology, phar macokinetics, the cardiovascular system, or cell interaction, simulation can play a vital role in explaining the underlying processes and in enhancing our understanding of these processes. This book comprises an excellent collection of contributions, and clearly demonstrates the value of simulation in the particular areas of physiology and bioengineering. My main frustration when teaching these classes to people with little or no computer background was the lack of suitable simulation software. This di rectly inspired my own attempts at producing software usable by the computer novice. It is especially nice that software is available that enables readers to experience the examples in this book for themselves. I would like to congratulate and thank the editors, Rogier P. van Wijk van Brievingh and Dietmar P. P. Moller, for all of their excellent efforts. They should be proud of their achievement. This is the sixth volume in the Advances in Simulation series, and other volumes are in preparation.