1771 search results - page 34 / 355 » Bayesian Network Based XP Process Modelling |
PKDD
2010
Springer
13 years 7 months ago
2010
Springer
Abstract. Bayesian reinforcement learning (RL) is aimed at making more efficient use of data samples, but typically uses significantly more computation. For discrete Markov Decis...
NIPS
2007
13 years 10 months ago
2007
Dynamic Bayesian networks are structured representations of stochastic processes. Despite their structure, exact inference in DBNs is generally intractable. One approach to approx...
JAIR
2008
13 years 8 months ago
2008
This paper presents Networks of Influence Diagrams (NID), a compact, natural and highly expressive language for reasoning about agents' beliefs and decision-making processes....
EWSN
2008
Springer
14 years 8 months ago
2008
Springer
In this paper3 , we use Bayesian Networks as a means for unsupervised learning and anomaly (event) detection in gas monitoring sensor networks for underground coal mines. We show t...
IPMU
2010
Springer
13 years 7 months ago
2010
Springer
It is well known that among all probabilistic graphical Markov models the class of decomposable models is the most advantageous in the sense that the respective distributions can b...