Abstract: In one embodiment, a method includes accessing policy states associated with a policy, determining that a particular policy state of the policy states should not be pruned, and generating possible next policy states for the particular policy state based on one or more policy actions and one or more costs associated with the respective policy actions, wherein each policy action 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.

Abstract: In one embodiment, a method includes accessing policy states associated with a policy, determining that a particular policy state of the policy states should not be pruned, and generating possible next policy states for the particular policy state based on one or more policy actions and one or more costs associated with the respective policy actions, wherein each policy action 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.

Abstract: Technology for improving evaluation of policies comprising multiple rules is disclosed. By generating a policy evaluation tree controlling, for any given policy state, which rules should be evaluated next, policy optimization can be performed off-line prior to policy evaluation. For a policy, a policy evaluation tree can be generated such that each node in the tree corresponds to a policy state and each child node corresponds to a policy state that may result from an action that may be taken from its parent policy state. Policy evaluation trees may be generated by iteratively generating, from an initial policy state, possible next states as child states until a result of the policy is determined. Some next possible policy states may be pruned from the tree based on conditions such as having a high cost of evaluation compared to the likelihood a rule will yield an interesting result.

Abstract: Technology for policies with reduced associated costs is disclosed. A policy may include an ordered rule set. When evaluated, the highest priority rule in the order that does not skip may control the policy outcome. Rules within a policy may have associated costs, such as data fetch and evaluation costs. In some contexts, it may be less important to evaluate every rule than to evaluate the policy quickly. Reduced policies that have one or more rules removed or that skip evaluation of some rules may be created for these contexts. When a rule of a policy is skipped, it may result in a possibility of a false allow or false deny. In some cases, rules may be duplicative. Removal or skipping of duplicative rules does not increase the possibility of a false allow or false deny. By using reduced policies in identified contexts, policy evaluation costs may be reduced.

Abstract: Technology for policies with reduced associated costs is disclosed. A policy may include an ordered rule set. When evaluated, the highest priority rule in the order that does not skip may control the policy outcome. Rules within a policy may have associated costs, such as data fetch and evaluation costs. In some contexts, it may be less important to evaluate every rule than to evaluate the policy quickly. Reduced policies that have one or more rules removed or that skip evaluation of some rules may be created for these contexts. When a rule of a policy is skipped, it may result in a possibility of a false allow or false deny. In some cases, rules may be duplicative. Removal or skipping of duplicative rules does not increase the possibility of a false allow or false deny. By using reduced policies in identified contexts, policy evaluation costs may be reduced.

Abstract: Technology for policies with reduced associated costs is disclosed. A policy may include an ordered rule set. When evaluated, the highest priority rule in the order that does not skip may control the policy outcome. Rules within a policy may have associated costs, such as data fetch and evaluation costs. In some contexts, it may be less important to evaluate every rule than to evaluate the policy quickly. Reduced policies that have one or more rules removed or that skip evaluation of some rules may be created for these contexts. When a rule of a policy is skipped, it may result in a possibility of a false allow or false deny. In some cases, rules may be duplicative. Removal or skipping of duplicative rules does not increase the possibility of a false allow or false deny. By using reduced policies in identified contexts, policy evaluation costs may be reduced.

Abstract: Technology for improving evaluation of policies comprising multiple rules is disclosed. By generating a policy evaluation tree controlling, for any given policy state, which rules should be evaluated next, policy optimization can be performed off-line prior to policy evaluation. For a policy, a policy evaluation tree can be generated such that each node in the tree corresponds to a policy state and each child node corresponds to a policy state that may result from an action that may be taken from its parent policy state. Policy evaluation trees may be generated by iteratively generating, from an initial policy state, possible next states as child states until a result of the policy is determined. Some next possible policy states may be pruned from the tree based on conditions such as having a high cost of evaluation compared to the likelihood a rule will yield an interesting result.

Abstract: Technology for policies with reduced associated costs is disclosed. A policy may include an ordered rule set. When evaluated, the highest priority rule in the order that does not skip may control the policy outcome. Rules within a policy may have associated costs, such as data fetch and evaluation costs. In some contexts, it may be less important to evaluate every rule than to evaluate the policy quickly. Reduced policies that have one or more rules removed or that skip evaluation of some rules may be created for these contexts. When a rule of a policy is skipped, it may result in a possibility of a false allow or false deny. In some cases, rules may be duplicative. Removal or skipping of duplicative rules does not increase the possibility of a false allow or false deny. By using reduced policies in identified contexts, policy evaluation costs may be reduced.