Relational decision theory, as presented in , is implemented in Alchemy as an option when the user calls the infer command. The input mln and evidence database are in the same format as when running inference. The option -decision must be specified, and the output is the optimal assignment to action atoms along with the utility achieved with the optimal assignment.
In Markov Logic Decision Networks (MLDNs), utility weights can be specified alongside probability weights in the following manner:
Here, we want to have a high utility if someone buys something, but the prior probability that someone actuall buys something is low. Utilities may also be specified in isolation after : if you don't want a weighted formula, but rather just want to specify a utility weight for an action predicate:
Here, we represent the cost of marketing something to someone.