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Cross-
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Cross-Disciplinary Experimentation

This research area will enable robustness and adaptation of perception, inference, and machine learning modalities to changing conditions and adversarial inputs, and adaptive behaviors that mitigate growing uncertainty in the heterogeneous models. Ultimately, constrained by the limited resources at the individual level, we will develop macro-scale cooperation and situational awareness in optempo missions with resilience to agent failures, network disruption, data loss, and/or compromised communications.

This research area addresses modeling of heterogeneous teams of humans, robots, sensors, tactical supercomputers, and tactical clouds that can be formed based on the context and the task. We will develop models of interactions between humans and other agents, and pursue formal approaches to composition of controllers, estimators and planners to design architectures and synthesize group behaviors.

This research area focuses on contextual abstractions to learn perception-action-