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» How to Dynamically Merge Markov Decision Processes
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FGR
2006
IEEE
205views Biometrics» more  FGR 2006»
15 years 3 months ago
Tracking Using Dynamic Programming for Appearance-Based Sign Language Recognition
We present a novel tracking algorithm that uses dynamic programming to determine the path of target objects and that is able to track an arbitrary number of different objects. The...
Philippe Dreuw, Thomas Deselaers, David Rybach, Da...
AAAI
2006
14 years 11 months ago
Point-based Dynamic Programming for DEC-POMDPs
We introduce point-based dynamic programming (DP) for decentralized partially observable Markov decision processes (DEC-POMDPs), a new discrete DP algorithm for planning strategie...
Daniel Szer, François Charpillet
VTC
2008
IEEE
173views Communications» more  VTC 2008»
15 years 4 months ago
Adaptive Call Admission Control with Dynamic Resource Reallocation for Cell-Based Multirate Wireless Systems
—This paper studies the admission control and resource allocation in a cell-based wireless system that supports singlemedia and multirate services. Utilizing the idea of adaptive...
Kai-Wei Ke, Chen-Nien Tsai, Ho-Ting Wu, Chia-Hao H...
CORR
2008
Springer
91views Education» more  CORR 2008»
14 years 9 months ago
Significant Diagnostic Counterexamples in Probabilistic Model Checking
Abstract. This paper presents a novel technique for counterexample generation in probabilistic model checking of Markov chains and Markov Decision Processes. (Finite) paths in coun...
Miguel E. Andrés, Pedro R. D'Argenio, Peter...
IROS
2009
IEEE
206views Robotics» more  IROS 2009»
15 years 4 months ago
Bayesian reinforcement learning in continuous POMDPs with gaussian processes
— Partially Observable Markov Decision Processes (POMDPs) provide a rich mathematical model to handle realworld sequential decision processes but require a known model to be solv...
Patrick Dallaire, Camille Besse, Stéphane R...