We suggest you first try to model it simply with pen and paper. Once you are happy with the model,
you should write the model in the .BIFXML format. See the README.md file of the git repository
for a more detailed description of the format. There you can also find some examples. Once you have
written it in .BIFXML format, you should be able to use the implementation of your reasoner to answer
interesting queries. For example, if you modeled a ”traffic” model, you could query the probability of
being late for work given it is rainy and a weekend. Make sure you include at least:
•an a-priori marginal query.
•a posterior marginal query.
•one MAP and one MEP query.
We want you to report a diagramm + CPTs of the variables in the report (6pts). This should come
along with a thorough explanation of the various variables and why you came up with the CPTs (8pts).
You also have to report about the queries you investigated. You should discuss whether the results
correspond with your expectation and document interesting insights the queries gave into your modeled
problem (6pts).
JoshuaSeth
commented
2 years ago
We suggest you first try to model it simply with pen and paper. Once you are happy with the model, you should write the model in the .BIFXML format. See the README.md file of the git repository for a more detailed description of the format. There you can also find some examples. Once you have written it in .BIFXML format, you should be able to use the implementation of your reasoner to answer interesting queries. For example, if you modeled a ”traffic” model, you could query the probability of being late for work given it is rainy and a weekend. Make sure you include at least: •an a-priori marginal query. •a posterior marginal query. •one MAP and one MEP query. We want you to report a diagramm + CPTs of the variables in the report (6pts). This should come along with a thorough explanation of the various variables and why you came up with the CPTs (8pts). You also have to report about the queries you investigated. You should discuss whether the results correspond with your expectation and document interesting insights the queries gave into your modeled problem (6pts).