Difference between revisions of "Pattern theory"

Revision as of 14:37, 6 September 2016

Pattern theory, formulated by Ulf Grenander, is a mathematical formalism to describe knowledge of the world as patterns.

Description

Pattern theory differs from other approaches to artificial intelligence in that it does not begin by prescribing algorithms and machinery to recognize and classify patterns; rather, it prescribes a vocabulary to articulate and recast the pattern concepts in precise language.

In addition to the new algebraic vocabulary, its statistical approach is novel in its aim to:

• Identify the hidden variables of a data set using real world data rather than artificial stimuli, which was previously commonplace.
• Formulate prior distributions for hidden variables and models for the observed variables that form the vertices of a Gibbs-like graph.
• Study the randomness and variability of these graphs.
• Create the basic classes of stochastic models applied by listing the deformations of the patterns.
• Synthesize (sample) from the models, not just analyze signals with it.

Broad in its mathematical coverage, Pattern Theory spans algebra and statistics, as well as local topological and global entropic properties.

The Brown University Pattern Theory Group was formed in 1972 by Ulf Grenander. Many mathematicians are currently working in this group, noteworthy among them being the Fields Medalist David Mumford. Mumford regards Grenander as his "guru" in this subject.

See also

• Abductive reasoning
• Algebraic statistics
• Formal concept analysis
• Formalism (philosophy of mathematics)
• Grammar Induction
• Image analysis
• Induction
• Lattice theory
• Spatial statistics

External links

• Pattern theory @ Wikipedia