com.cra.figaro.algorithm.decision
DecisionImportance
A sample consists of a weight and a map from elements to their values.
A sample consists of a weight and a map from elements to their values.
Called when the algorithm is killed.
Called when the algorithm is killed. By default, does nothing. Can be overridden.
Cleans up the temporary elements created during sampling.
Return an estimate of the expectation of the function under the marginal probability distribution of the target.
Return an estimate of the expectation of the function under the marginal probability distribution of the target.
Return an estimate of the expectation of the function under the marginal probability distribution of the target.
Return an estimate of the expectation of the function under the marginal probability distribution of the target.
Return an estimate of the probability of the predicate under the marginal probability distribution of the target.
Return an estimate of the probability of the predicate under the marginal probability distribution of the target.
Compute the utility of each parent/decision tuple and return a DecisionSample.
Compute the utility of each parent/decision tuple and return a DecisionSample. Each decision algorithm must define how this is done since it is used to set the policy for a decision. For sampling algorithms, this will me a map of parent/decision tuples to a utility and a weight for that combination. For factored algorithms, the DecisionSample will contain the exact expected utility with a weight of 1.0.
Return an estimate of the marginal probability distribution over the target that lists each element with its probability.
Return an estimate of the marginal probability distribution over the target that lists each element with its probability. The result is a lazy stream. It is up to the algorithm how the stream is ordered. Throws NotATargetException if called on a target that is not in the list of targets of the algorithm. Throws AlgorithmInactiveException if the algorithm is inactive.
Return an estimate of the expectation of the function under the marginal probability distribution of the target.
Return an estimate of the expectation of the function under the marginal probability distribution of the target. Throws NotATargetException if called on a target that is not in the list of targets of the algorithm. Throws AlgorithmInactiveException if the algorithm is inactive.
Total weight of samples taken.
Total weight of samples taken.
Get the total utility and weight for a specific value of a parent and decision.
Get the total utility and weight for a specific value of a parent and decision.
Get the total utility and weight for all sampled values of the parent and decision.
Get the total utility and weight for all sampled values of the parent and decision.
Called when the algorithm is started before running any steps.
Called when the algorithm is started before running any steps. By default, does nothing. Can be overridden.
Kill the algorithm so that it is inactive.
Kill the algorithm so that it is inactive. It will no longer be able to provide answers.Throws AlgorithmInactiveException if the algorithm is not active.
Return the mean of the probability density function for the given continuous element.
Return the mean of the probability density function for the given continuous element.
Return an element representing the posterior probability distribution of the given element.
Return an element representing the posterior probability distribution of the given element.
Return an estimate of the probability that the target produces the value.
Return an estimate of the probability that the target produces the value. Throws NotATargetException if called on a target that is not in the list of targets of the algorithm. Throws AlgorithmInactiveException if the algorithm is inactive.
Return an estimate of the probability of the predicate under the marginal probability distribution of the target.
Return an estimate of the probability of the predicate under the marginal probability distribution of the target. Throws NotATargetException if called on a target that is not in the list of targets of the algorithm. Throws AlgorithmInactiveException if the algorithm is inactive.
Resume the computation of the algorithm, if it has been stopped.
Resume the computation of the algorithm, if it has been stopped. Throws AlgorithmInactiveException if the algorithm is not active.
Produce one weighted sample of the given element.
Produce one weighted sample of the given element. weightedSample takes into account conditions and constraints on all elements in the Universe, including those that depend on this element.
For decisions, our weight is actually the weight of the sampled state times the sum of the utility nodes. This will be used as the "weight" in the weighted sampler, ie, we are accumulating the expected utility of each state. Note that the weights will not be normalized, but that is ok since strategies are an optimization and everything will be divided by a constant.
Sets the policy for the given decision.
Sets the policy for the given decision. This will get the computed utility of the algorithm and call setPolicy on the decision. Note there is no error checking here, so the decision in the argument must match the target decision in the algorithm.
Start the algorithm and make it active.
Start the algorithm and make it active. After it returns, the algorithm must be ready to provide answers. Throws AlgorithmActiveException if the algorithm is already active.
Stop the algorithm from computing.
Stop the algorithm from computing. The algorithm is still ready to provide answers after it returns. Throws AlgorithmInactiveException if the algorithm is not active.
Return the variance of the probability density function for the given continuous element.
Return the variance of the probability density function for the given continuous element.
Importance sampling for decisions. Almost the exact same as normal importance sampling except that it keeps track of utilities and probabilities (to compute expected utility) and it implements DecisionAlgorithm trait.