Sciweavers

1084 search results - page 158 / 217
» Hidden Markov Models with Multiple Observation Processes
Sort
View
ICRA
2010
IEEE
133views Robotics» more  ICRA 2010»
15 years 2 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
13 years 6 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...
ICML
2007
IEEE
16 years 4 months ago
Conditional random fields for multi-agent reinforcement learning
Conditional random fields (CRFs) are graphical models for modeling the probability of labels given the observations. They have traditionally been trained with using a set of obser...
Xinhua Zhang, Douglas Aberdeen, S. V. N. Vishwanat...
DAGM
2009
Springer
15 years 10 months ago
Optimal Parameter Estimation with Homogeneous Entities and Arbitrary Constraints
Abstract. Well known estimation techniques in computational geometry usually deal only with single geometric entities as unknown parameters and do not account for constrained obser...
Jochen Meidow, Wolfgang Förstner, Christian B...
GECCO
2003
Springer
100views Optimization» more  GECCO 2003»
15 years 9 months ago
Studying the Advantages of a Messy Evolutionary Algorithm for Natural Language Tagging
The process of labeling each word in a sentence with one of its lexical categories (noun, verb, etc) is called tagging and is a key step in parsing and many other language processi...
Lourdes Araujo