A Framework for Solving Hybrid Influence Diagrams Containing Deterministic Conditional Distributions

@article{Li2012AFF,
  title={A Framework for Solving Hybrid Influence Diagrams Containing Deterministic Conditional Distributions},
  author={Yijing Li and Prakash P. Shenoy},
  journal={Decision Analysis},
  year={2012},
  volume={9},
  pages={55-75}
}
  • Yijing Li, Prakash P. Shenoy
  • Published in Decision Analysis 2012
  • Mathematics, Computer Science
  • We describe a framework and an algorithm for approximately solving a class of hybrid influence diagrams (IDs) containing discrete and continuous chance variables, discrete and continuous decision variables, and deterministic conditional distributions for chance variables. A conditional distribution for a chance variable is said to be deterministic if its variances, for each state of its parents, are all zeroes. The solution algorithm is an extension of Shenoy's fusion algorithm for discrete… CONTINUE READING

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    References

    Publications referenced by this paper.
    SHOWING 1-10 OF 41 REFERENCES

    Valuation-Based Systems for Bayesian Decision Analysis

    VIEW 5 EXCERPTS

    Influence Diagrams with Continuous Decision Variables and Non-Gaussian Uncertainties

    VIEW 7 EXCERPTS
    HIGHLY INFLUENTIAL

    Representing and Solving Decision Problems with Limited Information

    VIEW 4 EXCERPTS
    HIGHLY INFLUENTIAL

    Inference in hybrid Bayesian networks using mixtures of polynomials

    VIEW 6 EXCERPTS

    Factor graphs and the Sum-Product Algorithm

    VIEW 4 EXCERPTS
    HIGHLY INFLUENTIAL

    Proximal Decision Analysis

    VIEW 3 EXCERPTS
    HIGHLY INFLUENTIAL