The scope and limits of simulation in automated reasoning

Ernest Davis, Gary Marcus

Research output: Contribution to journalReview articlepeer-review


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 article, we address the scope and limits of the use of simulation, with respect to AI tasks that involve high-level physical reasoning. We 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. We discuss twelve features of physical reasoning problems that pose challenges for simulation-based reasoning. We briefly survey alternative techniques for physical reasoning that do not rely on simulation.

Original languageEnglish (US)
Pages (from-to)60-72
Number of pages13
JournalArtificial Intelligence
StatePublished - Apr 2016


  • Physical reasoning
  • Simulation

ASJC Scopus subject areas

  • Language and Linguistics
  • Linguistics and Language
  • Artificial Intelligence


Dive into the research topics of 'The scope and limits of simulation in automated reasoning'. Together they form a unique fingerprint.

Cite this