Applying advanced technologies for performing data analytics, modeling, & simulations.

How We Do It
Charles F. Day and Associates

Reference World – Information Synthetic Environment v 4.0 (Reference World or RWISE) is a Data Science Machine Learning Artificial Intelligence (DS/ML/AI) driven Modeling & Simulation as a Service (MSaaS). It has been used to model societal structures, networks, social nuances, and behaviors to simulate different decision effects on different segments of society. RWISE’s M&S capability consists of three major components; 1) a “current state,” data lake that’s derived from the DSML ingested historical and real-time data which is made available for cross-domain analytics, 2) an integrated synthetic model bounded into a societal architecture with unique Artificial Intelligence methods, and, 3) an agent-based simulation engine that first creates a baseline forecast of the “future state” then is used to test potential policy actions for future effects to compare to the baseline. The “agents” may respond behaviorally to changes in their environment and may prompt changes within their networks during simulations. This is based on Nobel winner Daniel Kahneman’s Wellbeing Theory.

RWISE makes unique use of 21st-century data sciences and technologies to give users unparalleled insights of their world today and provide forecasts of tomorrow. Data sets from any realm of interest can be ingested into RWISE, creating a synthetic model from which you can run simulations by baselining the past and projecting trends forward. RWISE is the product of 20 years of progression in modeling and simulation, and agent-based modeling started with its predecessor platform known as Synthetic Environment for Analysis and Simulation (SEAS) Virtual International System (VIS). SEAS VIS and RWISE have been used by the U.S. Government, NATO, other countries, State, County, and City governments, Non-Profit.

Charles F. Day and Associates
Charles F. Day and Associates
Charles F. Day and Associates

RWISE Futures

Problem: The future is getting more complex and uncertain with faster rates of change. More Big Data is created, but it is generally outgrowing our ability to keep up, let alone put it to use.

Solution: Combine all the domain-relevant Big Data (whatever your domains of interest) with Artificial Intelligence, Machine Learning, and Agent-Based Modeling to create “Reference Worlds” where you can integrate your data, perform all your analyses, and test strategies into the future.