Uncertainty in Artificial Intelligence

Uncertainty in Artificial Intelligence

Proceedings of the Tenth Conference on Uncertainty in Artificial Intelligence, University of Washington, Seattle, July 29-31, 1994

1st Edition - July 1, 1994

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  • Author: MKP
  • eBook ISBN: 9781483298603

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Uncertainty in Artificial Intelligence: Proceedings of the Tenth Conference (1994) covers the papers accepted for presentation at the Tenth Annual Conference on Uncertainty in Artificial Intelligence, held in Seattle, Washington on July 29-31, 1994. The book focuses on the processes, methodologies, and approaches involved in artificial intelligence, including approximations, computational methods, Bayesian networks, and probabilistic inference. The selection first offers information on ending-based strategies for part-of-speech tagging; an evaluation of an algorithm for inductive learning of Bayesian belief networks using simulated data sets; and probabilistic constraint satisfaction with non-Gaussian noise. The text then examines Laplace's method approximations for probabilistic inference in belief networks with continuous variables; computational methods, bounds, and applications of counterfactual probabilities; and approximation algorithms for the loop cutset problem. The book takes a look at learning in multi-level stochastic games with delayed information; properties of Bayesian belief network learning algorithms; and the relation between kappa calculus and probabilistic reasoning. The manuscript also elaborates on intercausal independence and heterogeneous factorization; evidential reasoning with conditional belief functions; and state-space abstraction for anytime evaluation of probabilistic networks. The selection is a valuable reference for researches interested in artificial intelligence.

Table of Contents

  • Ending-Based Strategies for Part-of-Speech Tagging

    An Evaluation of an Algorithm for Inductive Learning of Bayesian Belief Networks Using Simulated Data Sets

    Probabilistic Constraint Satisfaction with Non-Gaussian Noise

    A Bayesian Method Reexamined

    Laplace's Method Approximations for Probabilistic Inference in Belief Networks with Continuous Variables

    Generating New Beliefs from Old

    Counterfactual Probabilities: Computational Methods, Bounds and Applications

    Modus Ponens Generating Function in the Class of Λ-Valuations of Plausibility

    Approximation Algorithms for the Loop Cutset Problem

    Possibility and Necessity Functions Over Non-Classical Logics

    Exploratory Model Building

    Learning in Multi-Level Stochastic Games with Delayed Information

    Planning with External Events

    Properties of Bayesian Belief Network Learning Algorithms

    A Stratified Simulation Scheme for Inference in Bayesian Belief Networks

    Proposal: Interactive Media for Research in Uncertainty

    Efficient Estimation of the Value of Information in Monte Carlo Models

    Symbolic Probabilistic Inference in Large BN20 Networks

    Action Networks: A Framework for Reasoning About Actions and Change Under Uncertainty

    On the Relation Between Kappa Calculus and Probabilistic Reasoning

    A Structured, Probabilistic Representation of Action

    Integrating Planning and Execution in Stochastic Domains

    Localized Partial Evaluation of Belief Networks

    A Probablistic Model of Action for Least-Commitment Planning with Information Gathering

    Some Properties of Joint Probability Distributions

    An Ordinal View of Independence with Application to Plausible Reasoning

    Penalty Logic and its Link with Dempster-Shafer Theory

    Value of Evidence on Influence Diagrams

    Conditional Independence in Possibility Theory

    Backward Simulation in Bayesian Networks

    Learning Gaussian Networks

    On Testing Whether an Embedded Bayesian Network Represents a Probability Model

    Epsilon-Safe Planning

    Generating Bayesian Networks from Probablity Logic Knowledge Bases

    Abstracting Probabilistic Actions

    On Modal Logics for Qualitative Possibility in a Fuzzy Setting

    A New Look at Causal Independence

    Learning Bayesian Networks: The Combination of Knowledge and Statistical Data

    A Decision-Based View of Causality

    Probabilistic Description Logics

    An Experimental Comparison of Numerical and Qualitative Probabilistic Reasoning

    An Alternative Proof Method for Possibilistic Logic and its Application to Terminological Logics

    Possibilistic Conditioning and Propagation

    The Automated Mapping of Plans for Plan Recognition

    A Logic for Default Reasoning About Probabilities

    Optimal Junction Trees

    From Influence Diagrams to Junction Trees

    Reduction of Computational Complexity in Bayesian Networks Through Removal of Weak Dependences

    Using New Data to Refine a Bayesian Network

    Syntax-Based Default Reasoning as Probabilistic Model-Based Diagnosis

    Induction of Selective Bayesian Classifiers

    Fuzzy Geometric Relations to Represent Hierarchical Spatial Information

    Constructing Belief Networks to Evaluate Plans

    Operator Selection While Planning Under Uncertainty

    Model-Based Diagnosis with Qualitative Temporal Uncertainty

    Incremental Dynamic Construction of Layered Polytree Networks

    Models of Consensus for Multiple Agent Systems

    A Probabilistic Calculus of Actions

    Robust Planning in Uncertain Environments

    Anytime Decision Making with Imprecise Probabilities

    Three Approaches to Probability Model Selection

    Knowledge Engineering for Large Belief Networks

    Solving Asymmetric Decision Problems with Influence Diagrams

    Belief Maintenance in Bayesian Networks

    Belief Updating by Enumerating High-Probability Independence-Based Assignments

    Global Conditioning for Probabilistic Inference in Belief Networks

    Belief Induced by the Partial Knowledge of the Probabilities

    Ignorance and the Expressiveness of Single- and Set-Valued Probability Models of Belief

    A Probabilistic Approach to Hierarchical Model-Based Diagnosis

    Semigraphoids Are Two-Antecedental Approximations of Stochastic Conditional Independence Models

    Exceptional Subclasses in Qualitative Probability

    A Defect in Dempster-Shafer Theory

    State-Space Abstraction for Anytime Evaluation of Probabilistic Networks

    General Belief Measures

    Generating Graphoids from Generalised Conditional Probability

    On Axiomatization of Probabilistic Conditional Independencies

    Evidential Reasoning with Conditional Belief Functions

    Intercausal Independence and Heterogeneous Factorization

    Author Index

Product details

  • No. of pages: 614
  • Language: English
  • Copyright: © Morgan Kaufmann 1994
  • Published: July 1, 1994
  • Imprint: Morgan Kaufmann
  • eBook ISBN: 9781483298603

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