most citedCP-nets: A Tool for Representing and Reasoning withConditional Ceteris Paribus Preference Statements

881 citations · 968 across the 3 of their papers we have counts for

collaborators
Showing cs.AIShow all

26 papers · 1 filter

cs.AI2013125 cited

Proceedings of the Tenth Conference on Uncertainty in Artificial Intelligence (1994)

Ramon Lopez de Mantaras, David Poole

This is the Proceedings of the Tenth Conference on Uncertainty in Artificial Intelligence, which was held in Seattle, WA, July 29-31, 1994

cs.AI20133 cited

Towards Solving the Multiple Extension Problem: Combining Defaults and Probabilities

Eric Neufeld, David L Poole

The multiple extension problem arises frequently in diagnostic and default inference. That is, we can often use any of a number of sets of defaults or possible hypotheses to explai…

cs.AI2013

Probabilistic Semantics and Defaults

Eric Neufeld, David L Poole

There is much interest in providing probabilistic semantics for defaults but most approaches seem to suffer from one of two problems: either they require numbers, a problem default…

cs.AI2013

Can Uncertainty Management be Realized in a Finite Totally Ordered Probability Algebra?

Yang Xiang, Michael P. Beddoes, David L Poole

In this paper, the feasibility of using finite totally ordered probability models under Alelinnas's Theory of Probabilistic Logic [Aleliunas, 1988] is investigated. The general for…

cs.AI2013

A Dynamic Approach to Probabilistic Inference

Michael C. Horsch, David L. Poole

In this paper we present a framework for dynamically constructing Bayesian networks. We introduce the notion of a background knowledge base of schemata, which is a collection of pa…

cs.AI2013

High Level Path Planning with Uncertainty

Runping Qi, David L. Poole

For high level path planning, environments are usually modeled as distance graphs, and path planning problems are reduced to computing the shortest path in distance graphs. One maj…