This award supports the Third IFIP Working Conference on "Verified Software: Theories, Tools, and Experiments (VSTTE 2010)", August 16-19, 2010, hosted by Heriot-Watt University, Edinburgh Scotland. The construction of reliable software poses one of the most significant scientific and engineering challenges of the 21st century.

Abstract The objective of this proposal is to hold a grantees meeting on July 8-9, 2009 focused on the potential of cyber-physical systems and their impact on our lives.

This award is funded under the American Recovery and Reinvestment Act of 2009 (Public Law 111-5). Many of the future applications of systems and control that will pertain to cyber-physical systems are those related to problems of (possibly) distributed estimation and control of multiple agents (both sensors and actuators) over networks. Examples include areas such as distributed sensor networks, control of distributed autonomous agents, collision avoidance, distributed power systems, etc.

The objective of this research is to develop the theoretical foundations for understanding implicit and explicit communication within cyber-physical systems.

The objective of this research is to develop foundations for the newly emerging generation of networked cyber-physical systems. The approach is based on a distributed logic of cyber-physical systems together with distributed cross-layer control and optimization strategies to enabled local actions to maintain or improve the satisfaction of system goals. The framework will be implemented first in simulation, then on one of SRI's robot platforms, and demonstrated in the context of networked mobile robotic teams, a particularly challenging application.

The objective of this research is to address a fundamental question in cyber-physical systems: What is the ideal structure of systems that detect critical events such as earthquakes by using data from large numbers of sensors held and managed by ordinary people in the community? The approach is to develop theory about widely-distributed sense and respond systems, using dynamic and possibly unreliable networks using sensors and responders installed and managed by ordinary citizens, and to apply the theory to problems important to society, such as responding to earthquakes.

The objective of this research is to integrate user control with automated reflexes in the human-machine interface. The approach, taking inspiration from biology, analyzes control-switching issues in brain-computer interfaces. A nonhuman primate will perform a manual task while movement- and touch-related brain signals are recorded. While a robotic hand replays the movements, electronic signals will be recorded from touch sensors on the robot?s fingers, then mapped to touch-based brain signals, and used to give the subject tactile sensation via direct cortical stimulation.

The objective of this research is to develop models, methods and tools for capturing and processing of events and actions in cyber-physical systems (CPS) in a manner that does not violate the underlying physics or computational logic. The project approach uses a novel notion of cyber-physical objects (CPO) to capture the mobility and localization of computation in cyber-physical systems using recent advances in geolocation and the Internet infrastructure and supports novel methods for spatiotemporal resource discovery.

The objective of this research is to develop a framework for the development and deployment of next-generation medical systems consisting of integrated and cooperating medical devices. The approach is to design and implement an open-source medical device coordination framework and a model-based component oriented programming methodology for the device coordination, supported by a formal framework for reasoning about device behaviors and clinical workflows.

The objective of this research is to develop a real-time operating system for a virtual humanoid avatar that will model human behaviors such as visual tracking and other sensori-motor tasks in natural environments. This approach has become possible to test because of the development of theoretical tools in inverse reinforcement learning (IRL) that allow the acquisition of reward functions from detailed measurements of human behavior, together with technical developments in virtual environments and behavioral monitoring that allow such measurements to be obtained.