Intelligent automated planning system for large-scale operations

A computer-implemented method executed on an intelligent automated planning system for prediction of future performance of large-scale operations and to manage financial, operational and market execution risk, the computer implemented method comprising:

• instantiating a distributed directed computational graph comprising nodes representing data transformations and edges representing messages between the nodes, wherein:
• the directed computational graph comprises a data processing workflow for analyzing a large-scale operational plan and associated risk factors based on market, operations and financial data retrieved over the web from both corporate operations data stores and analogous previous venture outcome data stores;
• and
• the data transformation of one or more of the nodes comprises receipt of data from a physical sensor;
• storing the directed computational graph specified processing workflow;
• performing a plurality of analytic and simulation computations as directed by the data processing workflow of the directed computational graph;
• producing a first result comprising a plurality of estimated future states of the large-scale operational plan under at least one scenario over a finite time horizon;
• and
• producing a second result comprising at least one additional scenario and a second plurality of estimated future states associated with it, and a plurality of associated risk factors and their impact on the first and second pluralities of estimated future states.

A system for prediction of future performance of large-scale operations and to manage financial, operational and market execution risk employing an intelligent automated planning system, comprising one or more computers with executable instructions that, when executed, cause the system to:

• instantiate a distributed directed computational graph comprising nodes representing data transformations and edges representing messages between the nodes, wherein:
• the directed computational graph comprises a data processing workflow for analyzing a large-scale operational plan and associated risk factors based on market, operations and financial data retrieved over the web from both corporate operations data stores and other exogenous sources;
• and
• the data transformation of one or more of the nodes comprises receipt of data from at least one physical or virtual sensor or application telemetry source;
• store the directed computational graph specified processing workflow;
• perform a plurality of analytic and simulation computations as directed by the data processing workflow of the directed computational graph;
• produce a first result comprising a plurality of estimated future states of the large-scale operational plan under at least one scenario over a finite time horizon;
• and
• produce a second result comprising at least one additional scenario and a second plurality of estimated future states associated with it, and a plurality of associated risk factors and their impact on the first and second pluralities of estimated future states.

Non-transitory, computer-readable storage media having computer-executable instructions embodied thereon that, when executed by one or more processors of a computing system employing an intelligent automated planning system for prediction of future performance of large-scale operations and to manage financial, operational and market execution risk, cause the computing system to:

• instantiate a distributed directed computational graph comprising nodes representing data transformations and edges representing messages between the nodes, wherein:
• the directed computational graph comprises a data processing workflow for analyzing a large-scale operational plan and associated risk factors based on market, operations and financial data retrieved over the web from both corporate operations data stores and other exogenous sources;
• and
• the data transformation of one or more of the nodes comprises receipt of data from at least one physical or virtual sensor or application telemetry source;
• store the directed computational graph specified processing workflow;
• perform a plurality of analytic and simulation computations as directed by the data processing workflow of the directed computational graph;
• produce a first result comprising a plurality of estimated future states of the large-scale operational plan under at least one scenario over a finite time horizon;
• and
• produce a second result comprising at least one additional scenario and a second plurality of estimated future states associated with it, and a plurality of associated risk factors and their impact on the first and second pluralities of estimated future states.