Cisco Technology, Inc.

Optumsoft, Inc.

Intel Corporation

Hicamp Systems, Inc.

Other

Leland Stanford Junior University

Oracle America, Inc.

Cisco Systems Inc.

David R. Cheriton

Hiscamp Systems, Inc.

David R Cheriton

Andreas V Bechtolsheim

Alexandre Y Solomatnikov

Amin Firoozshahian

Constantine P Sapuntzakis

Hugh Weber Holbrook

Kenneth J Duda

Aly E Orady

Shimon Muller

Ariel Hendel

Michael K Wong

Mohammad Kamel Issa

Yatin Gajjar

Fusun Ertemalp

Raju Penumatcha

Andy Bechtolsheim

A set of input conditions is obtained. A plurality of potential decisions is obtained based at least in part on the set of input conditions. A rule-based system is used to process the plurality of potential decisions and obtain a set of one or more updated potential decisions, wherein: the rule-based system specifies a plurality of rules; a rule specifies a rule condition and a corresponding action, wherein when the rule condition is met, the corresponding action is to be performed; and using the rule-based system to process the plurality of potential decisions includes: for a selected potential decision in the plurality of potential decisions, determining whether the rule condition is met for a selected rule among the plurality of rules, wherein the selected rule condition is dependent on, at least in part, the selected potential decision; and in response to the selected rule condition being met, performing the corresponding action. The set of one or more updated potential decisions to be executed is output.

Incorporating rules into complex automated decision making

A labelled point within a multidimensional space is input from a set of input records. It is determined whether the labelled point is subsumed by a member hyperregion of the set of hyperregions specified by an BSRS, wherein the BSRS includes a boundary-structured rule corresponding to a hyperregion in the multidimensional space. In the event the labelled point is not subsumed, the BSRS is expanded or the labelled point is eliminated.

Automatic approximating refinement of ruleset from labelled datasets

A first set of subconditions is obtained. Approximate matching of the first set of subconditions against a plurality of sets of subconditions is performed. A second set of subconditions among the plurality of sets of subconditions is accessed, wherein a representation of a subcondition in the first set and/or the second set of subconditions comprises a value having one of a plurality of states, and wherein the plurality of states comprises a state of 'don't care'. The first set of subconditions is approximately matched against the second set of subconditions. The first set of subconditions is compared against the second set of subconditions. A matching criterion is determined to be met based on a result of the matching. Information indicating that the second set of subconditions is at least an approximate match for the first set of subconditions is output.

Approximate matching

Automatically generating a rule set implementation is disclosed. A set of rules is accessed. For each non-const rule in the set of rules, one or more implication directed acyclic graphs (DAGs) are constructed. The non-const rule directly causes at least one external output or at least one external action. The one or more implication DAGs specify rule conditions, including one or more observable rule conditions. Implication DAGs that are constructed for the set of rules are compiled to obtain a compiled result that is configured to evaluate rule conditions associated with the set of rules and determine one or more actions when at least one of the rule conditions evaluates to true. The compiled result is output.

Automatic generation of an efficient rule set implementation

Specifications are input, comprising: a plurality of lanes in an environment for a controlled system; a plurality of lane maneuvers associated with the plurality of lanes; a plurality of lane subconditions associated with the controlled system; and a rule set comprising a plurality of rules, wherein a rule in the rule set specifies a rule condition and a rule action to take when the rule condition is satisfied, wherein the rule condition comprises a corresponding set of lane subconditions, and wherein the rule action comprises a corresponding lane maneuver. The controlled system is automatically navigated dynamically, at least in part by: monitoring the plurality of lane subconditions; evaluating rule conditions associated with the plurality of rules in the rule set to determine one or more rules whose corresponding rule conditions has been met; and executing one or more lane maneuvers that correspond to the one or more determined rules.

Using a lane-structured dynamic environment for rule-based automated control

A plurality of potential fault scenarios are accessed, wherein a given potential fault scenario of the plurality of potential fault scenarios has at least one corresponding root cause, and a representation of the given potential fault scenario comprises a don't care value. An actual fault scenario from telemetry received from a monitored system is generated. The actual fault scenario is matched against the plurality of potential fault scenarios. One or more matched causes are output as one or more probable root cause failures of the monitored system.

Automatic root cause analysis using ternary fault scenario representation

Possible input value combinations of a prediction of an engineered system are iterated over, comprising, for a possible input value combination: selecting an action to perform on the engineered system for the possible input value combination, comprising: performing a plurality of predictions of the engineered system scored by evaluating an objective function associated with the engineered system and using the possible input value combination and a corresponding plurality of actions. The action is selected from the corresponding plurality of actions, the selection being based at least in part on scores of the plurality of predictions. A rule specifying a corresponding set of one or more rule conditions that is met when the possible input value combination is matched and a corresponding action associated with the rule as a selected action is generated. The generated set of rules to be stored or further processed is output.

Automatic generation of control decision logic for complex engineered systems from dynamic physical model

A set of queries on a collection of data records is received. A set of subconditions required to support the set of queries is determined. An index table is maintained, wherein an entry in the index table indicates a subcondition status associated with a data record in the collection of data records. A specific query is received indicating a specified set of subcondition statuses. The specified set of subcondition statuses is matched against the index table. A result set is returned corresponding to matched rows in the index table, wherein the matched rows match the specified set of subcondition statuses.

Sparse data index table

Memory reclamation includes executing a process that has a plurality of objects, the objects being accessible via a plurality of references, at least some of the plurality of references being transient references, at least some of the plurality of references being persistent references; reaching a reclamation point at which a process state has no transient references, or has transient references only at known locations; and at the reclamation point, destructing objects that have no persistent references and no transient references.

Growing community of inventors

Palo Alto, CA, United States of America

David R Cheriton