AAAI
2012
12 years 1 months ago
2012
Markov decision processes (MDPs) are an established framework for solving sequential decision-making problems under uncertainty. In this work, we propose a new method for batchmod...
AAAI
2000
14 years 26 days ago
2000
This paper addresses the problem of tracking and diagnosing complex systems with mixtures of discrete and continuous variables. This problem is a difficult one, particularly when ...
UAI
2004
14 years 27 days ago
2004
Although many real-world stochastic planning problems are more naturally formulated by hybrid models with both discrete and continuous variables, current state-of-the-art methods ...
UAI
2001
14 years 27 days ago
2001
In this paper we present a method of computing the posterior probability of conditional independence of two or more continuous variables from data, examined at several resolutions...
UAI
2001
14 years 27 days ago
2001
Many real life domains contain a mixture of discrete and continuous variables and can be modeled as hybrid Bayesian Networks (BNs). An important subclass of hybrid BNs are conditi...
EUSFLAT
2003
14 years 27 days ago
2003
This paper proposes a method for Bayesian networks that handles uncertainty and discretization of continuous variables when learning the networks from a database of cases. The dat...
AAAI
2007
14 years 1 months ago
2007
Since Bayesian network (BN) was introduced in the field of artificial intelligence in 1980s, a number of inference algorithms have been developed for probabilistic reasoning. Ho...
HYBRID
2004
Springer
14 years 4 months ago
2004
Springer
In this paper we consider the problem of estimating discrete variables in a class of hybrid systems where we assume that the continuous variables are available for measurement. Usi...
HYBRID
2005
Springer
14 years 5 months ago
2005
Springer
We study the class of lazy linear hybrid automata with finite precision. The key features of this class are: – The observation of the continuous state and the rate changes assoc...
EPIA
2005
Springer
14 years 5 months ago
2005
Springer
This paper presents an adaptation of the peepholing method to regression trees. Peepholing was described as a means to overcome the major computational bottleneck of growing classi...