Defense Advanced Research Projects AgencyTagged Content List

Artificial Intelligence and Human-Computer Symbiosis Technologies

Technology to facilitate more intuitive interactions between humans and machines

Showing 6 results for Artificial Intelligence + ML RSS
In this thematic episode of the Voices from DARPA podcast, three program managers discuss the possibility that emerging technologies in the arena of artificial intelligence (AI) are converging toward an “artificial science” toolset that could open an era we might designate as Science 2.0. The prospect of AI scientists making Nobel-prize-caliber discoveries is not around the corner, but it is a distinct possibility for the future, suggests program manager Jiangying Zhou of the agency’s Defense Sciences Office (DSO).
In order to transform machine learning systems from tools into partners, users need to trust their machine counterpart. One component to building a trusted relationship is knowledge of a partner’s competence (an accurate insight into a partner’s skills, experience, and reliability in dynamic environments). While state-of-the-art machine learning systems can perform well when their behaviors are applied in contexts similar to their learning experiences, they are unable to communicate their task strategies, the completeness of their training relative to a given task, the factors that may influence their actions, or their likelihood to succeed under specific conditions.
The Physics of Artificial Intelligence (PAI) program is part of a broad DAPRA initiative to develop and apply “Third Wave” AI technologies to sparse data and adversarial spoofing, and that incorporate domain-relevant knowledge through generative contextual and explanatory models.
Current artificial intelligence (AI) systems excel at tasks defined by rigid rules – such as mastering the board games Go and chess with proficiency surpassing world-class human players. However, AI systems aren’t very good at adapting to constantly changing conditions commonly faced by troops in the real world – from reacting to an adversary’s surprise actions, to fluctuating weather, to operating in unfamiliar terrain.
Serial Interactions in Imperfect Information Games Applied to Complex Military Decision Making (SI3-CMD) builds on recent developments in artificial intelligence and game theory to enable more effective decisions in adversarial domains. SI3-CMD will explore several military decision making applications at strategic, tactical, and operational levels and develop AI/game theory techniques appropriate for their problem characteristics.