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Titlebook: AI 2010: Advances in Artificial Intelligence; 23rd Australasian Jo Jiuyong Li Conference proceedings 2011 The Editor(s) (if applicable) and

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The Decoding of Eukaryotic Genomes,datatype (nominal and numerical, but also structured). We present a way of graphically representing the original stochastic probability estimation trees using a user-friendly gravitation simile.We include experiments showing that Newton trees outperform other PETs in probability estimation and accuracy.
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https://doi.org/10.1007/978-3-642-17432-2computational intelligence; data mining; intelligent agents; machine learning; natural language processi
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Kimberly Maich,Darren Levine,Carmen Hall automatically gain knowledge about new games that follows from the rules without being explicitly given. In this paper, we show how a recently developed, theoretical method for automated theorem proving in general game playing can be put into practice. To this end, we extend the method so as to all
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https://doi.org/10.1007/978-3-030-68549-2iefs as a pre-order over terms. We define a belief revision operator via minimising the change of the prime implicants of the existing beliefs and the incoming information with respect to agent’s preferences. We show that such a belief revision operator satisfies Katsuno and Mendelzon’s postulates f
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Functional Analysis of Violence–Aggression Bayesian conditionalization. We show that this naturally leads to a rational account of probabilistic belief removal – a rather long standing problem in the area. It turns out that our generalization of imaging indeed is an account of probabilistic belief erasure as opposed to probabilistic belief
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