Abstract
In this paper we give a simple account of local computation of marginal probabilities when the joint probability distribution is given in factored form and the sets of variables involved in the factors form a hypertree. Previous expositions of such local computation have emphasized conditional probability. We believe this emphasis is misplaced. What is essential to local computation is a factorization. It is not essential that this factorization be interpreted in terms of conditional probabilities. The account given here avoids the divisions required by conditional probabilities and generalizes readily to alternative measures of subjective probability, such as Dempster-Shafer or Spohnian belief functions.
Original language | English (US) |
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Pages (from-to) | 327-351 |
Number of pages | 25 |
Journal | Annals of Mathematics and Artificial Intelligence |
Volume | 2 |
Issue number | 1-4 |
DOIs | |
State | Published - Mar 1990 |
Externally published | Yes |
All Science Journal Classification (ASJC) codes
- Artificial Intelligence
- Applied Mathematics
Keywords
- Markov tree
- Probability propagation
- array
- construction sequence
- hypertree
- hypertree cover
- local computation
- parallel processing
- potential