Abstract: Scientific challenges: How can multiple cooperative cyber-physical systems communicate and coordinate to accomplish complex high-level tasks within unknown, dynamic and adversarial environments?

Abstract: The objective of this project is to develop a theoretical framework for stochastic learning, decision-making, and control in high-dimensional cyber-physical systems. In our general framework, decision makers dynamically refine their estimates of the time-varying physical system based on acquired information, which may be obtained by distributed sensors.

Abstract: CyberPhysical Systems (CPS) that self-modify to improve performance or repair damage often rewrite the modular relationships that make system modeling or Verification and Validation (V&V) possible. In this project, we are exploring methods to create self- modifying CPS systems that, in addition to self-improving or self-repairing, are also capable of maintaining system models that support the use of V&V techniques.