Capital One Services, LLC

Matthew Tomaszewicz

Francisco Gutierrez

Eiran Shalev

Sandeep Narayanaswami

A system, method, and computer-readable medium for generating factual and/or counterfactual data are described. This may have the effect of improving the complexity of data available for training machine learning models. The models may include agent-based models (ABMs) in which the agent definitions are decoupled from the simulation. In one or more aspects, some agents may have attributes and associated behaviors that permit them to be reused in different ABMs to simulate different systems.

Extensible agents in agent-based generative models

A system, method, and computer-readable medium for generating factual and/or counterfactual data are described. This may have the effect of improving the complexity of data available for training machine learning models. The models may include, but not limited to, a probabilistic graphical model (PGM) and/or an agent-based model (ABM). Further aspects may provide for scrubbing actual data to create a data model that does not reveal the content of the underlying source data. Yet further aspects may provide for validating a data model.

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San Francisco, CA, United States of America

Matthew Tomaszewicz