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AAAI
1997
15 years 8 months ago
Incremental Methods for Computing Bounds in Partially Observable Markov Decision Processes
Partially observable Markov decision processes (POMDPs) allow one to model complex dynamic decision or control problems that include both action outcome uncertainty and imperfect ...
Milos Hauskrecht
CDC
2008
IEEE
16 years 1 months ago
Shannon meets Bellman: Feature based Markovian models for detection and optimization
— 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 ...
Sean P. Meyn, George Mathew
COMCOM
2006
89views more  COMCOM 2006»
15 years 6 months ago
Quantifying the effects of recent protocol improvements to TCP: Impact on Web performance
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
ICRA
2009
IEEE
111views Robotics» more  ICRA 2009»
16 years 1 months ago
Model-based and model-free reinforcement learning for visual servoing
— 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...
IROS
2008
IEEE
105views Robotics» more  IROS 2008»
16 years 29 days ago
Consensus-based task sequencing in decentralized multiple-robot systems using local communication
— 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...
Chris A. C. Parker, Hong Zhang