Partially observable Markov decision processes (POMDPs) allow one to model complex dynamic decision or control problems that include both action outcome uncertainty and imperfect ...
— The goal of this paper is to develop modeling techniques for complex systems for the purposes of control, estimation, and inference: (i) A new class of Hidden Markov Models is ...
We assess the state of Internet congestion control and error recovery through a controlled study that considers the integration of standards-track TCP error recovery and both TCP ...
Michele C. Weigle, Kevin Jeffay, F. Donelson Smith
— To address the difficulty of designing a controller for complex visual-servoing tasks, two learning-based uncalibrated approaches are introduced. The first method starts by b...
Amir Massoud Farahmand, Azad Shademan, Martin J&au...
— Behavior-based controllers for complex missions often are more easily designed by decomposing the mission into a series of smaller subtasks. When applying this technique to a m...