AAAI
2012
12 years 2 months ago
2012
Planning under uncertainty is an important and challenging problem in multiagent systems. Multiagent Partially Observable Markov Decision Processes (MPOMDPs) provide a powerful fr...
AAAI
2012
12 years 2 months ago
2012
Penetration Testing is a methodology for assessing network security, by generating and executing possible hacking attacks. Doing so automatically allows for regular and systematic...
CSL
2012
Springer
12 years 8 months ago
2012
Springer
Reinforcement techniques have been successfully used to maximise the expected cumulative reward of statistical dialogue systems. Typically, reinforcement learning is used to estim...
AAAI
2011
13 years 13 days ago
2011
Recently, a number of researchers have proposed spectral algorithms for learning models of dynamical systems—for example, Hidden Markov Models (HMMs), Partially Observable Marko...
AIED
2011
Springer
13 years 4 months ago
2011
Springer
Both human and automated tutors must infer what a student knows and plan future actions to maximize learning. Though substantial research has been done on tracking and modeling stu...
COLING
2010
13 years 7 months ago
2010
This paper investigates how to automatically create a dialogue control component of a listening agent to reduce the current high cost of manually creating such components. We coll...
PKDD
2010
Springer
13 years 10 months ago
2010
Springer
Partially observable Markov decision processes (POMDPs) are widely used for planning under uncertainty. In many applications, the huge size of the POMDP state space makes straightf...
ICTAI
2010
IEEE
13 years 10 months ago
2010
IEEE
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...
NN
2010
Springer
13 years 11 months ago
2010
Springer
We present a model-free reinforcement learning method for partially observable Markov decision problems. Our method estimates a likelihood gradient by sampling directly in paramet...
IJRR
2010
13 years 11 months ago
2010
Partially observable Markov decision processes (POMDPs) provide a principled, general framework for robot motion planning in uncertain and dynamic environments. They have been app...