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ICML
2006
IEEE
14 years 8 months ago
Probabilistic inference for solving discrete and continuous state Markov Decision Processes
Inference in Markov Decision Processes has recently received interest as a means to infer goals of an observed action, policy recognition, and also as a tool to compute policies. ...
Marc Toussaint, Amos J. Storkey
NIPS
2008
13 years 9 months ago
Fitted Q-iteration by Advantage Weighted Regression
Recently, fitted Q-iteration (FQI) based methods have become more popular due to their increased sample efficiency, a more stable learning process and the higher quality of the re...
Gerhard Neumann, Jan Peters
CVPR
2011
IEEE
13 years 3 months ago
Learning Context for Collective Activity Recognition
In this paper we present a framework for the recognition of collective human activities. A collective activity is defined or reinforced by the existence of coherent behavior of i...
Wongun Choi, Silvio Savarese, Khuram Shahid
ICRA
2007
IEEE
126views Robotics» more  ICRA 2007»
14 years 2 months ago
A formal framework for robot learning and control under model uncertainty
— While the Partially Observable Markov Decision Process (POMDP) provides a formal framework for the problem of robot control under uncertainty, it typically assumes a known and ...
Robin Jaulmes, Joelle Pineau, Doina Precup
JAIR
2008
121views more  JAIR 2008»
13 years 7 months ago
A Constraint Programming Approach for Solving a Queueing Control Problem
In a facility with front room and back room operations, it is useful to switch workers between the rooms in order to cope with changing customer demand. Assuming stochastic custom...
Daria Terekhov, J. Christopher Beck