Policy evaluation trees

One or more computer-readable non-transitory storage media embodying software that is operable when executed to:

• access a plurality of policy states associated with a policy;
• determine that a particular policy state of the plurality of policy states should not be pruned;
• and
• generate, for the particular policy state, possible next policy states based on one or more policy actions and one or more costs associated with the respective one or more policy actions, wherein each of the one or more policy actions is associated with one or more probabilities corresponding to one or more possibilities of resulting in one or more of the possible next policy states, wherein the respective cost associated with the policy action is determined based on one or more computing costs of the policy action resulting in the one or more of the possible next policy states in combination with the respective one or more probabilities, and wherein each policy state of the created policy evaluation tree comprises a rule state for each rule of the policy.

A system comprising:

• one or more processors;
• and a non-transitory memory coupled to the processors comprising instructions executable by the processors, the processors operable when executing the instructions to:
• access a plurality of policy states associated with a policy;
• determine that a particular policy state of the plurality of policy states should not be pruned;
• and
• generate, for the particular policy state, possible next policy states based on one or more policy actions and one or more costs associated with the respective one or more policy actions, wherein each of the one or more policy actions is associated with one or more probabilities corresponding to one or more possibilities of resulting in one or more of the possible next policy states, wherein the respective cost associated with the policy action is determined based on one or more computing costs of the policy action resulting in the one or more of the possible next policy states in combination with the respective one or more probabilities, and wherein each policy state of the created policy evaluation tree comprises a rule state for each rule of the policy.