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» Learning Partially Observable Deterministic Action Models
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ATAL
2004
Springer
14 years 1 months ago
Communication for Improving Policy Computation in Distributed POMDPs
Distributed Partially Observable Markov Decision Problems (POMDPs) are emerging as a popular approach for modeling multiagent teamwork where a group of agents work together to joi...
Ranjit Nair, Milind Tambe, Maayan Roth, Makoto Yok...
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
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...
PRL
2006
115views more  PRL 2006»
13 years 7 months ago
A hybrid parallel projection approach to object-based image restoration
Approaches analyzing local characteristics of an image prevail in image restoration. However, they are less effective in cases of restoring images degraded by large size point spr...
Xin Fan, Hua Huang, Dequn Liang, Chun Qi
LOGCOM
2011
12 years 10 months ago
Introducing Preferences in Planning as Satisfiability
Planning as Satisfiability is one of the most well-known and effective techniques for classical planning: satplan has been the winning system in the deterministic track for optim...
Enrico Giunchiglia, Marco Maratea