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AAAI
2012
8 years 2 months ago
Kernel-Based Reinforcement Learning on Representative States
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...
Branislav Kveton, Georgios Theocharous
AAAI
2000
10 years 1 months ago
Bayesian Fault Detection and Diagnosis in Dynamic Systems
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 ...
Uri Lerner, Ronald Parr, Daphne Koller, Gautam Bis...
UAI
2004
10 years 1 months ago
Solving Factored MDPs with Continuous and Discrete Variables
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 ...
Carlos Guestrin, Milos Hauskrecht, Branislav Kveto...
UAI
2001
10 years 1 months ago
A Bayesian Multiresolution Independence Test for Continuous Variables
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...
Dimitris Margaritis, Sebastian Thrun
UAI
2001
10 years 1 months ago
Exact Inference in Networks with Discrete Children of Continuous Parents
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...
Uri Lerner, Eran Segal, Daphne Koller
EUSFLAT
2003
152views Fuzzy Logic» more  EUSFLAT 2003»
10 years 1 months ago
Bayesian networks for continuous values and uncertainty in the learning process
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...
J. F. Baldwin, E. Di Tomaso
AAAI
2007
10 years 2 months ago
Unscented Message Passing for Arbitrary Continuous Variables in Bayesian Networks
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...
Wei Sun, Kuo-Chu Chang
HYBRID
2004
Springer
10 years 5 months ago
Discrete State Estimators for a Class of Hybrid Systems on a Lattice
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...
Domitilla Del Vecchio, Richard M. Murray
HYBRID
2005
Springer
10 years 5 months ago
The Discrete Time Behavior of Lazy Linear Hybrid Automata
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...
Manindra Agrawal, P. S. Thiagarajan
EPIA
2005
Springer
10 years 5 months ago
Adapting Peepholing to Regression Trees
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...
Luís Torgo, Joana Marques
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