Paul B. Reverdy
Human-in-the-loop control systems
Vehicle dynamics and control
I study how humans and automated systems can work together to complete physical tasks. Often these tasks are expressed as optimization problems. The humans interact with the automated system by defining the objective function to be optimized, by providing information about the structure of the problem, and sometimes by approving and implementing the actions recommended by the automated system. By combining the ability of humans to learn structure from experience and the ability of automated algorithms to carry out computation and process data, I develop systems that achieve higher performance than either humans or automation could achieve on their own.
My Ph.D. thesis
A dynamical system for prioritizing and coordinating motivations
Submitted; preprint available on arXiv.
Satisficing in multi-armed bandit problems
IEEE Transactions on Automatic Control, August 2017 (to appear, with V. Srivastava and N.E. Leonard)
Parameter estimation in softmax decision-making models with linear objective functions
IEEE Transactions on Automation Science and Engineering, 13(1), 54-67. (with N.E. Leonard)
Algorithmic models of human decision making in Gaussian multi-armed bandit problems
Proc. of the European Control Conference, 2210-2215, 2014. (with V. Srivastava and N.E. Leonard)
Recipient of the Best Student Paper Award, ECC 2014.
Modeling human decision-making in generalized Gaussian multi-armed bandits
Proceedings of the IEEE, April 2014
Modeling human decision-making in multi-armed bandits
Multidisciplinary Conf. on Reinforcement Learning and Decision Making, Princeton, NJ, USA, October 2013
On optimal foraging and multi-armed bandits
Proc. 51st Annual Allerton Conference on Communication, Control and Computing, 2013
Towards optimization of a human-inspired heuristic for solving explore-exploit problems
Proc. IEEE Conference on Decision and Control, 2012
Underwater robotics at the Dynamical Systems Control Laboratory, Princeton
MAE Generals Binders
Investing for Technical Majors article, October 2010 revision.