Continuous Decision MTE Influence Diagrams
نویسنده
چکیده
منابع مشابه
Decision making with hybrid influence diagrams using mixtures of truncated exponentials
Mixtures of truncated exponentials (MTE) potentials are an alternative to discretization for representing continuous chance variables in influence diagrams. Also, MTE potentials can be used to approximate utility functions. This paper introduces MTE influence diagrams, which can represent decision problems without restrictions on the relationships between continuous and discrete chance variable...
متن کاملHybrid Influence Diagrams Using Mixtures of Truncated Exponentials
Mixtures of truncated exponentials (MTE) potentials are an alternative to discretization for representing continuous chance variables in influence diagrams. Also, MTE potentials can be used to approximate utility functions. This paper introduces MTE influence diagrams, which can represent decision problems without restrictions on the relationships between continuous and discrete chance variable...
متن کاملA Bayesian Network Framework for the Construction of Virtual Agents with Human-like Behaviour
• Complexity Results for Enhanced Qualitative Probabilistic Networks. Johan Kwisthout and Gerard Tel • Preprocessing the MAP Problem. Janneke H. Bolt and Linda C. van der Gaag • An Empirical Study of Efficiency and Accuracy of Probabilistic Graphical Models. Jens D. Nielsen and Manfred Jaeger • Sensitivity analysis of extreme inaccuracies in Gaussian Bayesian Networks. Miguel A. Gómez-Villegas,...
متن کاملA Review of Representation Issues and Modeling Challenges with Influence Diagrams
Since their introduction in the mid 1970s, influence diagrams have become a de facto standard for representing Bayesian decision problems. The need to represent complex problems has led to extensions of the influence diagram methodology designed to increase the ability to represent complex problems. In this paper, we review the representation issues and modeling challenges associated with influ...
متن کاملSolving Hybrid Influence Diagrams with Deterministic Variables
We describe a framework and an algorithm for solving hybrid influence diagrams with discrete, continuous, and deterministic chance variables, and discrete and continuous decision variables. A continuous chance variable in an influence diagram is said to be deterministic if its conditional distributions have zero variances. The solution algorithm is an extension of Shenoy’s fusion algorithm for ...
متن کامل