The Defense Advanced Research Projects Agency (DARPA) is seeking proposals to address challenges in artificial intelligence (AI) algorithms and architectures that deeply integrate symbolic reasoning with data-driven machine learning to create robust, assured, and, therefore, trustworthy AI-based systems.

Despite recent improvements to machine learning algorithms and assurance technologies, high levels of autonomy remain elusive. According to DARPA officials, the reason behind this is twofold:

  • data-driven machine learning lacks transparency, interpretability, and robustness and has unsustainable computational and data needs; and
  • traditional approaches to building intelligent applications and autonomous systems that rely on knowledge representations and symbolic reasoning can be assured but are not robust to the uncertainties encountered in the real world.

“Motivating new thinking and approaches in this space will help assure that autonomous systems will operate safely and perform as intended,” said Sandeep Neema, DARPA ANSR program manager, in a press release. “This will be integral to trust, which is key to the Department of Defense’s successful adoption of autonomy.”

DARPA is seeking proposals under its newest AI program, the Assured Neuro Symbolic Learning and Reasoning (ANSR) program, to address these challenges in the form of new, hybrid (neuro-symbolic) AI algorithms that deeply integrate symbolic reasoning with data-driven learning to create robust, assured, and therefore trustworthy systems.

The overarching goal of the ANSR program is to advance hybrid AI algorithms and develop evidence-based techniques that support confident assurance judgments for these algorithms.

The program intends to explore “diverse hybrid architectures that can be seeded with prior knowledge, acquire both statistical and symbolic knowledge through learning, and adapt learned representations,” the program announcement noted.

In addition, the program intends to demonstrate and evaluate hybrid AI techniques through mission-relevant use-cases where assurance and autonomy are mission-critical.

Selected teams will develop a common operating picture of a dynamic, dense urban environment using a fully autonomous system equipped with ANSR technologies. The AI would deliver insights to the warfighter that could help characterize friendly, adversarial, and neutral entities, the operating environment, and threat and safety corridors.

All proposed research should investigate innovative approaches that enable revolutionary advances in science, devices, or systems. DARPA is specifically excluding research that primarily results in evolutionary improvements to the existing state of practice.

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Lisbeth Perez
Lisbeth Perez
Lisbeth Perez is a MeriTalk Senior Technology Reporter covering the intersection of government and technology.