STOCHASTIC PROCESS DECISION METHODS FOR COMPLEX CYBER-PHYSICAL SYSTEMS The primary objective of our effort is to develop a fundamental theory to quantify the inherent uncertainties and risks in complex system design and development processes. These theoretical developments will help enable the achievement of the META goal of devising, implementing, and demonstrating in practice a radically different approach to the design, integration/manufacturing, and verification of complex systems. Our approach to meeting this objective is: to adapt the entropy concepts of information theory to create a metric for system complexity; to apply estimation theory to characterize inherent uncertainty in system development processes; and to utilize this theoretical base to develop efficient methods for resource allocation so as to manage uncertainty and mitigate risk in complex system developments. K . Willcox, D. Allaire, J. Deyst, C. He, and G. Sondecker 
 Massachusetts Institute of Technology