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 year = {2018},
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 pages = {100-116},
 websites = {http://arxiv.org/abs/1902.05479},
 publisher = {College Publicacions},
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 abstract = {It may happen that for a certain abductive problem there are several possible explanations, not all of them mutually compatible. What explanation is selected and which criteria are used to select it? This is the well-known problem of the selection of abductive hypotheses. Are there criteria that can help us to select the simplest explanation in a broad spectrum of abductive problems? To give an (affirmative) answer to this question we will move to a field in theoretical computer science: Algorithmic Information Theory (AIT). The algorithmic complexity measure K(s) can be used to determine which is the best theory within those explaining a set of observations. We introduce an application of K(s) to the selection of the best abductive explanation, in the context of dynamic epistemic logic (DEL).},
 bibtype = {inbook},
 author = {Soler-Toscano, Fernando},
 editor = {Freund, Max A. and Ruffino, Marco and Fernandez de Castro, Max},
 chapter = {Which is the least complex explanation? Abduction and complexity},
 title = {Logic and Philosophy of Logic. Recent Trends in Latin America and Spain}
}

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