Jump to content

Model-based reasoning

From Wikipedia, the free encyclopedia
This is an old revision of this page, as edited by Commander Keane bot (talk | contribs) at 17:41, 30 November 2005 (Robot-assisted disambiguation (you can help!): model). The present address (URL) is a permanent link to this revision, which may differ significantly from the current revision.

In artificial intelligence, model-based reasoning refers to an inference method used in expert systems based on a model of the physical world.

Knowledge represenation

In a model-based reasoning system knowledge is repesented unsing causal rules. For example, in a medical diagnosis system the knowledge base may contain the following rule:

∀ patients : Stroke(patient) → Confused(patient) ∧ Unequal(Pupils(patient))

In contrast in a diagnostic reasoning system knowledge would be represented through diagnostic rules such as:

∀ patients : Confused(patient) → Stroke(patient)
∀ patients : Unequal(Pupils(patient)) → Stroke(patient)

References

  • Stuart J. Russel, Peter Norvig; Artificial Intelligence: A Modern Approach 2nd edition; Prentice Hall (2003); ISBN 0-13-080302-2.