I study a model of dynamic policy making in which citizens do not have complete knowledge of how policies are mapped into outcomes. They learn about the mapping through repeated elections as policies are implemented and outcomes observed. I characterize for this environment the policy trajectory with impatient voters. I find that through experimentation good policies are frequently found. Howev...

Continuous-time Markov chains are used to model systems in which transitions between states as well as the time the system spends in each state are random. Many computational problems related to such chains have been solved, including determining state distributions as a function of time, parameter estimation, and control. However, the problem of inferring most likely trajectories, where a traj...

Predicting the future course of a moving target is invaluable for planning actions. We used trajectory detection in noise to investigate this predictive capability. Using a contrast probe technique, we showed that in noise, contrast increments are more easily seen at the end of the trajectory than at the beginning. Analyses of the contrast data revealed that the improvement at the end of the tr...

The Next Generation Air Transportation System (NextGen) is the solution to capacity, safety, and efficiency problems that will result from an expected increase in traffic. Trajectory-based operations are identified in the NextGen Concept of Operations as a key capability required to ensure the success of NextGen; thus, it is essential that the accuracy of trajectory prediction software be teste...

An optimal explicit guidance law that maximizes terminal velocity is developed for a reentry vehicle to a fixed target. The equations of motion are reduced with differential flatness approach and acceleration commands are related to trajectory’s parameters. An optimal trajectory is determined by solving a real-coded genetic algorithm. For online trajectory generation, optimal trajectory is appr...