In scientific computing and in realistic graphic animation, simulation — that is, step-by-step calculation of the complete trajectory of a physical system — is one of the most common and important modes of calculation.
In this talk, Ernest Davis of New York University will address the scope and limits of the use of simulation, with respect to artificial intelligence (AI) tasks that involve high-level physical reasoning. He will argue that, in many cases, simulation can play at most a limited role. Simulation is most effective when the task is prediction, when complete information is available, when a reasonably high-quality theory is available, and when the range of scales involved, both temporal and spatial, is not extreme. When these conditions do not hold, simulation is less effective or entirely inappropriate.
Ernest will discuss twelve features of physical reasoning problems that pose challenges for simulation-based reasoning, and will briefly survey alternative techniques for physical reasoning that do not rely on simulation.