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ICRA
2010
IEEE
133views Robotics» more  ICRA 2010»
13 years 6 months ago
Variable resolution decomposition for robotic navigation under a POMDP framework
— Partially Observable Markov Decision Processes (POMDPs) offer a powerful mathematical framework for making optimal action choices in noisy and/or uncertain environments, in par...
Robert Kaplow, Amin Atrash, Joelle Pineau
ICTAI
2010
IEEE
13 years 5 months ago
A Closer Look at MOMDPs
Abstract--The difficulties encountered in sequential decisionmaking problems under uncertainty are often linked to the large size of the state space. Exploiting the structure of th...
Mauricio Araya-López, Vincent Thomas, Olivi...
ICMLA
2008
13 years 9 months ago
Prediction-Directed Compression of POMDPs
High dimensionality of belief space in Partially Observable Markov Decision Processes (POMDPs) is one of the major causes that severely restricts the applicability of this model. ...
Abdeslam Boularias, Masoumeh T. Izadi, Brahim Chai...
AAAI
2012
11 years 10 months ago
POMDPs Make Better Hackers: Accounting for Uncertainty in Penetration Testing
Penetration Testing is a methodology for assessing network security, by generating and executing possible hacking attacks. Doing so automatically allows for regular and systematic...
Carlos Sarraute, Olivier Buffet, Jörg Hoffman...
ECAI
2010
Springer
13 years 8 months ago
On Finding Compromise Solutions in Multiobjective Markov Decision Processes
A Markov Decision Process (MDP) is a general model for solving planning problems under uncertainty. It has been extended to multiobjective MDP to address multicriteria or multiagen...
Patrice Perny, Paul Weng