Artificial intelligence decision modeling processes using analytics and data shapely for multiple stakeholders

Abstract

Data Shapley is an approach to understand the role of data in a decision-making process. The present invention involves a process to connect Data Shapley to a data analytics and machine learning based decision-making environment through the use of utility functions. In the present invention a problem is structurally analyzed using machine learning and data analytics to determine structural trends. Data is then analyzed using Data Shapley to determine what additional information is needed to make a decision. This allows for the relevant data to be collected to estimate utility functions for participants. Data Shapley is then used again to decompose the decision-making process and look for trends in the process, and machine learning is applied to see if there are commonalities across the criteria in the decision-making process. After this, the decision-making process selects a strategy as the decision. If new information becomes available or an event occurs that makes a change of strategy necessary, then Data Shapley is used to guide the data acquisition and decision-making process. If no new information is available or an event does not occur, event occurrence is dynamically predicted using data analytics and Data Shapley proactively recommends what data streams to monitor and collect.

Dependencies are inferred from the claim text.