Decision analysis networks

Francisco Javier Díez, Manuel Luque, Iñigo Bermejo
<span title="">2018</span> <i title="Elsevier BV"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/sy2zvsxl4vdejh3zsp3utmplry" style="color: black;">International Journal of Approximate Reasoning</a> </i> &nbsp;
This paper presents decision analysis networks (DANs) as a new type of probabilistic graphical model. Like influence diagrams (IDs), DANs are much more compact and easier to build than decision trees, and are able to represent conditional independencies. Both IDs and DANs can represent symmetric problems, but DANs can also represent problems involving restrictions between the values of the variables (structural asymmetry) and partial orderings of the decisions (order asymmetry). Therefore, DANs
more &raquo; ... can easily model and solve many real-world problems that IDs cannot. We argue that DANs compare favorably with other formalisms proposed for modeling asymmetric decision problems. Additionally, we offer Open-Markov as an open source software tool for editing and evaluating DANs.
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1016/j.ijar.2018.02.007">doi:10.1016/j.ijar.2018.02.007</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/6rdtipqgfbabjfsgusaensgamu">fatcat:6rdtipqgfbabjfsgusaensgamu</a> </span>
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