Influence diagram policy evaluation

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ale.mnc
Posts: 9
Joined: Tue Jul 11, 2017 8:45 am

Influence diagram policy evaluation

Post by ale.mnc »

Hello,

I am working on an influence diagram to identify the optimal policy on multiple decision nodes.
Can you provide further information about the computational time of the algorithm by Cooper (1988) [section 5.7.7.1 of GeNIe manual]?
Specifically, are you aware of any research investigating the computational time of the algorithm based on the number of decision nodes?

Alessandro
shooltz[BayesFusion]
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Joined: Mon Nov 26, 2007 5:51 pm

Re: Influence diagram policy evaluation

Post by shooltz[BayesFusion] »

Specifically, are you aware of any research investigating the computational time of the algorithm based on the number of decision nodes?
In both influence diagrams and Bayesian networks, the number of nodes is not sufficient to estimate the computational time. The complexity depends on number of nodes, number of outcomes and the topology of the network.
ale.mnc
Posts: 9
Joined: Tue Jul 11, 2017 8:45 am

Re: Influence diagram policy evaluation

Post by ale.mnc »

Thank you, are you aware of any study investigating the computational time according to these factors?
marek [BayesFusion]
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Re: Influence diagram policy evaluation

Post by marek [BayesFusion] »

If you are interested in the complexity of the Cooper's algorithm, you should look at the complexity of probabilistic inference and the factors that influence it. There is a sea of literature on this topic. Cooper's algorithm, as implemented in GeNIe and SMILE, first converts the ID to a Bayesian network and then performs as many updates as are needed to evaluate all possible policies. The number of possible policies is roughly a product of the number of decision options in each of the decision nodes and each chance node that is observed before a decision node. I hope this helps.
Cheers,

Marek
ale.mnc
Posts: 9
Joined: Tue Jul 11, 2017 8:45 am

Re: Influence diagram policy evaluation

Post by ale.mnc »

Perfect, thank you!
Alessandro
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