David L Poole

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Professor of Computer Science at University of British Columbia

Towards Solving the Multiple Extension Problem: Combining Defaults and Probabilities

The multiple extension problem arises frequently in diagnostic and defau...
03/27/2013 ∙ by Eric Neufeld, et al. ∙ 0 ∙ share

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Probabilistic Semantics and Defaults

There is much interest in providing probabilistic semantics for defaults...
03/27/2013 ∙ by Eric Neufeld, et al. ∙ 0 ∙ share

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

In this paper, the feasibility of using finite totally ordered probabili...
03/27/2013 ∙ by Yang Xiang, et al. ∙ 0 ∙ share

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A Dynamic Approach to Probabilistic Inference

In this paper we present a framework for dynamically constructing Bayesi...
03/27/2013 ∙ by Michael C. Horsch, et al. ∙ 0 ∙ share

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What is an Optimal Diagnosis?

Within diagnostic reasoning there have been a number of proposed definit...
03/27/2013 ∙ by David L Poole, et al. ∙ 0 ∙ share

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High Level Path Planning with Uncertainty

For high level path planning, environments are usually modeled as distan...
03/20/2013 ∙ by Runping Qi, et al. ∙ 0 ∙ share

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Representing Bayesian Networks within Probabilistic Horn Abduction

This paper presents a simple framework for Horn clause abduction, with p...
03/20/2013 ∙ by David L Poole, et al. ∙ 0 ∙ share

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Sidestepping the Triangulation Problem in Bayesian Net Computations

This paper presents a new approach for computing posterior probabilities...
03/13/2013 ∙ by Nevin Lianwen Zhang, et al. ∙ 0 ∙ share

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Exploring Localization in Bayesian Networks for Large Expert Systems

Current Bayesian net representations do not consider structure in the do...
03/13/2013 ∙ by Yang Xiang, et al. ∙ 0 ∙ share

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Incremental computation of the value of perfect information in stepwise-decomposable influence diagrams

To determine the value of perfect information in an influence diagram, o...
03/06/2013 ∙ by Nevin Lianwen Zhang, et al. ∙ 0 ∙ share

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The use of conflicts in searching Bayesian networks

This paper discusses how conflicts (as used by the consistency-based dia...
03/06/2013 ∙ by David L Poole, et al. ∙ 0 ∙ share

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Inter-causal Independence and Heterogeneous Factorization

It is well known that conditional independence can be used to factorize ...
02/27/2013 ∙ by Nevin Lianwen Zhang, et al. ∙ 0 ∙ share

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Solving Asymmetric Decision Problems with Influence Diagrams

While influence diagrams have many advantages as a representation framew...
02/27/2013 ∙ by Runping Qi, et al. ∙ 0 ∙ share

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A Framework for Decision-Theoretic Planning I: Combining the Situation Calculus, Conditional Plans, Probability and Utility

This paper shows how we can combine logical representations of actions a...
02/13/2013 ∙ by David L Poole, et al. ∙ 0 ∙ share

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Flexible Policy Construction by Information Refinement

We report on work towards flexible algorithms for solving decision probl...
02/13/2013 ∙ by Michael C. Horsch, et al. ∙ 0 ∙ share

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Context-Specific Approximation in Probabilistic Inference

There is evidence that the numbers in probabilistic inference don't real...
01/30/2013 ∙ by David L Poole, et al. ∙ 0 ∙ share

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An Anytime Algorithm for Decision Making under Uncertainty

We present an anytime algorithm which computes policies for decision pro...
01/30/2013 ∙ by Michael C. Horsch, et al. ∙ 0 ∙ share

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Estimating the Value of Computation in Flexible Information Refinement

We outline a method to estimate the value of computation for a flexible ...
01/23/2013 ∙ by Michael C. Horsch, et al. ∙ 0 ∙ share

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Reasoning With Conditional Ceteris Paribus Preference Statem

In many domains it is desirable to assess the preferences of users in a ...
01/23/2013 ∙ by Craig Boutilier, et al. ∙ 0 ∙ share

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Building a Stochastic Dynamic Model of Application Use

Many intelligent user interfaces employ application and user models to d...
01/16/2013 ∙ by Peter J. Gorniak, et al. ∙ 0 ∙ share

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Efficient Inference in Large Discrete Domains

In this paper we examine the problem of inference in Bayesian Networks w...
10/19/2012 ∙ by Rita Sharma, et al. ∙ 0 ∙ share

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Nonparametric Bayesian Logic

The Bayesian Logic (BLOG) language was recently developed for defining f...
07/04/2012 ∙ by Peter Carbonetto, et al. ∙ 0 ∙ share

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Constraint Processing in Lifted Probabilistic Inference

First-order probabilistic models combine representational power of first...
05/09/2012 ∙ by Jacek Kisynski, et al. ∙ 0 ∙ share

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Seeing the Forest Despite the Trees: Large Scale Spatial-Temporal Decision Making

We introduce a challenging real-world planning problem where actions mus...
05/09/2012 ∙ by Mark Crowley, et al. ∙ 0 ∙ share

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David L Poole

Featured Co-authors

Nando de Freitas

Craig Boutilier

Yang Xiang

Mark Crowley

Ronen I. Brafman

Nevin Lianwen Zhang

Holger H. Hoos

Gregory M. Provan

Michael C. Horsch

Peter Carbonetto

Jacek Kisynski

Towards Solving the Multiple Extension Problem: Combining Defaults and Probabilities

Probabilistic Semantics and Defaults

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

A Dynamic Approach to Probabilistic Inference

What is an Optimal Diagnosis?

High Level Path Planning with Uncertainty

Representing Bayesian Networks within Probabilistic Horn Abduction

Sidestepping the Triangulation Problem in Bayesian Net Computations

Exploring Localization in Bayesian Networks for Large Expert Systems

Incremental computation of the value of perfect information in stepwise-decomposable influence diagrams

The use of conflicts in searching Bayesian networks

Inter-causal Independence and Heterogeneous Factorization

Solving Asymmetric Decision Problems with Influence Diagrams

A Framework for Decision-Theoretic Planning I: Combining the Situation Calculus, Conditional Plans, Probability and Utility

Flexible Policy Construction by Information Refinement

Context-Specific Approximation in Probabilistic Inference

An Anytime Algorithm for Decision Making under Uncertainty

Estimating the Value of Computation in Flexible Information Refinement

Reasoning With Conditional Ceteris Paribus Preference Statem

Building a Stochastic Dynamic Model of Application Use

Efficient Inference in Large Discrete Domains

Nonparametric Bayesian Logic

Constraint Processing in Lifted Probabilistic Inference

Seeing the Forest Despite the Trees: Large Scale Spatial-Temporal Decision Making