Download Archie's Double Digest 155 (November 2004) by John Albano PDF

By John Albano

Archie's Double Digest #155 - November 2004

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Extra info for Archie's Double Digest 155 (November 2004)

Sample text

But when the same representation is supposed to be available to multiple processes, then representation realism implies a set of epistemological commitments about correlations or stabilities between predictions about the behaviors generated by the different processes. Process realism similarly implies epistemological commitments of interprediction correlations and stabilities, but this time for the same task given different inputs, backgrounds, or environmental conditions. That is, if one is committed to the reality of a given cognitive process, then that process should function similarly across a range of inputs and conditions.

The descendants of X are defined similarly. Of course, we are rarely interested in the graph solely as a mathematical object; rather, we want it to represent something, and so the semantics of the nodes and edges matter. , decision nodes in an influence diagram or decision network). The edges can similarly have different meanings, but the edge semantics always involve direct relevance, whether direct causation, a direct communication or social connection, direct probabilistic relevance, or some other sort of direct connection.

This chapter introduces and explores the framework of graphical models, the computational and mathematical basis of that architecture. The main thread of the chapter focuses on a conceptual introduction, with mathematical details provided in sections marked with an asterisk (*); the reader can skip those sections with little loss of (qualitative) understanding. 1 explores the common elements shared by all graphical models, with subsequent sections examining the details of specific model types. As with many formal frameworks, a highlevel grasp of different graphical model types suffices to understand most uses of them.

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