### Abstract

The construction of causal graphs from non-experimental data rests on a set of constraints that the graph structure imposes on all probability distributions compatible with the graph. These constraints are of two types: conditional independencies and algebraic constraints, first noted by Verma. While conditional independencies are well studied and frequently used in causal induction algorithms, Verma constraints are still poorly understood, and rarely applied. In this paper we examine a special subset of Verma constraints which are easy to understand, easy to identify and easy to apply; they arise from "dormant independencies," namely, conditional independencies that hold in interventional distributions. We give a complete algorithm for determining if a dormant independence between two sets of variable!; is entailed by the causal graph, such that this independence is identifiable, in other words if it resides in an interventional distribution that can be predicted without resorting to interventions. We further show the usefulness of dormant independencies in model testing and induction by giving an algorithm that uses constraints entailed by dormant independencies to prune extraneous edges from a given causal graph.

Original language | English (US) |
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Title of host publication | AAAI-08/IAAI-08 Proceedings - 23rd AAAI Conference on Artificial Intelligence and the 20th Innovative Applications of Artificial Intelligence Conference |

Pages | 1081-1087 |

Number of pages | 7 |

State | Published - Dec 24 2008 |

Event | 23rd AAAI Conference on Artificial Intelligence and the 20th Innovative Applications of Artificial Intelligence Conference, AAAI-08/IAAI-08 - Chicago, IL, United States Duration: Jul 13 2008 → Jul 17 2008 |

### Publication series

Name | Proceedings of the National Conference on Artificial Intelligence |
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Volume | 2 |

### Other

Other | 23rd AAAI Conference on Artificial Intelligence and the 20th Innovative Applications of Artificial Intelligence Conference, AAAI-08/IAAI-08 |
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Country | United States |

City | Chicago, IL |

Period | 7/13/08 → 7/17/08 |

### ASJC Scopus subject areas

- Software
- Artificial Intelligence

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## Cite this

*AAAI-08/IAAI-08 Proceedings - 23rd AAAI Conference on Artificial Intelligence and the 20th Innovative Applications of Artificial Intelligence Conference*(pp. 1081-1087). (Proceedings of the National Conference on Artificial Intelligence; Vol. 2).