When loops are present, the network is no longer singly connected and local propagation schemes will invariably run into trouble.. If we ignore the e… - Judea Pearl

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When loops are present, the network is no longer singly connected and local propagation schemes will invariably run into trouble.. If we ignore the existence of loops and permit the nodes to continue communicating with each other as if the network were singly connected, messages may circulate indefinitely around the loops and process may not converges to a stable equilibrium... Such oscillations do not normally occur in probabilistic networks... which tend to bring all messages to some stable equilibrium as time goes on. However, this asymptotic equilibrium is not coherent, in the sense that it does not represent the posterior probabilities of all nodes of the network.

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About Judea Pearl

(born 1936) is an Israeli-born American computer scientist and philosopher, best known for championing the probabilistic approach to artificial intelligence and the development of . He is the 2011 winner of the ACM Turing Award, the highest distinction in computer science, "for fundamental contributions to artificial intelligence through the development of a calculus for probabilistic and causal reasoning."

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Native Name: יהודה פרל
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Traditional statistics is strong in devising ways of describing data and inferring distributional parameters from sample. Causal inference requires two additional ingredients: a science-friendly language for articulating causal knowledge, and a mathematical machinery for processing that knowledge, combining it with data and drawing new causal conclusions about a phenomenon.

Haavelmo was the first to recognize the capacity of economic models to guide policies. This paper describes some of the barriers that Haavelmo’s ideas have had (and still have) to overcome, and lays out a logical framework that has evolved from Haavelmo’s insight and matured into a coherent and comprehensive account of the relationships between theory, data and policy questions. The mathematical tools that emerge from this framework now enable investigators to answer complex policy and counterfactual questions using simple routines, some by mere inspection of the model’s structure.

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