Probabilistic Reasoning in Intelligent Systems

Pearl, J. (1988). Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference. Morgan Kaufmann.

Type

Book

Intellectual base

Review or monograph

Year

1988

DOI

10.1016/c2009-0-27609-4

ISBN

9780080514895

DOI registrant

Elsevier

Link

https://dl.acm.org/doi/book/10.5555/534975

Cited from

cognitive_science, statistics_experimental_design

Cited by

4 citations across 4 artifacts.

Each citation links to the sentence it supports in the citing article.

Primes

• Bayesian Updating

  • This sourceMorgan Kaufmann. Formalizes Bayesian belief networks and the propagation calculus by which probabilistic inference, sensor fusion, and explanatory revision share a single substrate-neutral update mechanism.

• Belief Formation
  • The structural insight is robust: a child revising "all four-legged animals are dogs" upon encountering a cat, a juror shifting from undecided to "guilty" through deliberation, a Bayesian agent updating a posterior distribution upon receiving an observation, and a scientific community gradually accepting plate tectonics over decades all exhibit the same commitment-transition logic, a cross-substrate generalization Pearl (1988) established in formalizing belief networks where probabilistic inference, sensor fusion, and explanatory revision share one update calculus.

    This sourceFormalizes Bayesian belief networks and the propagation calculus by which probabilistic inference, sensor fusion, and explanatory revision share one substrate-neutral update mechanism.

• Markov Blanket
  • In a directed graphical model the blanket consists of the node's parents, its children, and its children's other parents; in an undirected graph it is the node's immediate neighbors.

    This sourceIntroduces the Markov blanket of a node (parents, children, children's co-parents) as the minimal set rendering it conditionally independent of the rest of the network, and grounds belief propagation.

Domain-specific

• Probabilistic Graphical Model
  • The invariant is not one edge style; it is a disciplined graph-to-probability correspondence.

Verification

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Links previously used in the corpus

Before the registry existed this work was also linked 1 other way.

• https://doi.org/10.1016/C2009-0-27609-4 ×1

Registry ID ref:74a19cdf86e2 · see in the full table