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Charles River Analytics Working with Raytheon BBN on AI and Machine Learning Effort for DARPA

DARPA effort will help military planners understand and address conflict

Charles River Analytics Inc., developer of intelligent systems solutions, is working with Raytheon BBN to develop modeling software that helps military planners understand and address conflict. Charles River Analytics and Raytheon BBN will use artificial intelligence (AI) and machine learning to develop tools for the Defense Advanced Research Projects Agency (DARPA).

The US military has faced complex organizational environments and diverse enemies over the last fifteen years. Under the Causal Exploration of Complex Operational Environments (Causal Exploration) program, DARPA is developing modeling tools intended to help military planners understand and address the underlying causal factors that lead to these conflicts.

Charles River Analytics and Raytheon BBN Technologies are using AI and machine learning to extract information from open source and other data sets. With a deeper exploration of the causal dynamics of complex conflict conditions, military planners can develop a more informed understanding, and develop recommendations for courses of action that target the underlying cause of a conflict.

“We’re developing algorithms and software to efficiently mine data sources with diverse content, structure, scale, and quality for predictive and causal information,” explained David Blumstein, Senior Scientist and Charles River Principal Investigator on the effort. “These technologies will help users of the Causal Exploration platform rapidly construct decision-support models calibrated to individual operational environments.”

In a related effort for DARPA, Charles River is developing a tool to better measure deterrence strategies in the “Gray Zone.” More information on the BELIEVES effort can be found here.

This material is based upon work supported by a Raytheon BBN Technologies Corp. Subcontract under the United States Air Force Contract FA8650-17-C-7716. The views, opinions and/or findings expressed are those of the author and should not be interpreted as representing the official views or policies of the Department of Defense or the U.S. Government.

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