Computational Cognition and Machine Intelligence

Objective
This program supports innovative basic research on the fundamental principles and methodologies needed to enable intelligent machine behavior in support of autonomous and mixed-initiative (i.e., human-agent teaming) systems.  The overall vision of this program is that future computational systems will achieve high levels of performance, adaptation, flexibility, self-repair, and other forms of intelligent behavior in the complex, uncertain, adversarial, and highly dynamic environments faced by the U.S. Air Force.  This program draws from the full spectrum of models of intelligence, from cognitively plausible reasoning processes that are responsible for human performance in complex problem-solving and decision-making tasks, to non-cognitive computational models of intelligence necessary to create robust intelligent autonomous systems. In the midst of this spectrum are the technologies needed to seamlessly incorporate intelligent computational systems into mixed human-agent teams.  The program is divided into three sub-areas that span the full spectrum of computational and machine intelligence:

• Computational Cognition: supports innovative basic research on building computational systems that derive from and/or integrate cognitive and biological models of human and animal intelligence. The overall objective is to understand and exploit these processes to create computational models that perform as well as or better than the reasoning systems they emulate.
• Robust Decision Making:  supports new theoretical and empirical guidance needed to enable maximally effective mixtures of human and machine decision making in environments that are becoming increasingly complex and demanding as a result of the high uncertainty, complexity, time urgency, and rapidly changing nature of military missions.
• Machine Intelligence: supports innovative basic research on fundamental principles and methodologies of computational intelligence necessary to create robust intelligent autonomous systems. These methodologies are likely to be non-cognitive, taking full advantage of the strengths embodied in mathematical and computational systems, such as the ability of quickly manage vast amounts of data.

Solicitation
BAA-AFRL-AFOSR-2015-001

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Program Overview
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Contact Information
Dr. James H. Lawton
AFOSR/RTA2
Tele: (703) 696-5999
DSN: 426-5999
FAX: (703) 696-7360
Email: Machine.Itel@afosr.af.mil