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Simulation based progressions for learning aerial movements

✍ Scribed by M.R. Yeadon


Book ID
107781384
Publisher
Elsevier Science
Year
1993
Tongue
English
Weight
119 KB
Volume
26
Category
Article
ISSN
0021-9290

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The problem of learning Bayesian networks from statistical data is described and reformulated as a discrete optimization problem. For a solution we employ the stochastic algorithm that is known as simulated annealing and that is based on the Markov Chain Monte Carlo approach. Numerical examples are