Artículos con la etiqueta ‘inducción’

Dos aspectos del razonamiento abductivo

Por • 24 jul, 2013 • Category: Opinion

Discuto dos aspectos del reciente libro de Atocha Aliseda sobre el razonamiento abductivo. El primero tiene que ver con la clasificación de la abducción propuesta por Aliseda respecto al tipo de lógica que le subyace. El segundo se refiere al mecanismo de búsqueda de hipótesis abductivas que nos ofrece Aliseda.



On Tarski’s fixed point theorem

Por • 21 ene, 2013 • Category: Opinion

A concept of abstract inductive definition on a complete lattice is formulated and studied. The theory of abstract inductive definitions generalizes the theory, due to Aczel, of inductive definitions on a set. As an application, a constructive and predicative version of Tarski’s fixed point theorem is obtained.



Open Problems in Universal Induction & Intelligence

Por • 12 jul, 2012 • Category: Ciencia y tecnología

Specialized intelligent systems can be found everywhere: finger print, handwriting, speech, and face recognition, spam filtering, chess and other game programs, robots, et al. This decade the first presumably complete mathematical theory of artificial intelligence based on universal induction-prediction-decision-action has been proposed. This informationtheoretic approach solidifies the foundations of inductive inference and artificial intelligence. Getting the foundations right usually marks a significant progress and maturing of a field. The theory provides a gold standard and guidance for researchers working on intelligent algorithms. The roots of universal induction have been laid exactly half-a-century ago and the roots of universal intelligence exactly one decade ago. So it is timely to take stock of what has been achieved and what remains to be done. Since there are already good recent surveys, I describe the state-of-the-art only in passing and refer the reader to the literature. This article concentrates on the open problems in universal induction and its extension to universal intelligence.



Bayesian Causal Induction

Por • 16 nov, 2011 • Category: Educacion

Discovering causal relationships is a hard task, often hindered by the need for intervention, and often requiring large amounts of data to resolve statistical uncertainty. However, humans quickly arrive at useful causal relationships. One possible reason is that humans use strong prior knowledge; and rather than encoding hard causal relationships, they encode beliefs over causal structures, allowing for sound generalization from the observations they obtain from directly acting in the world. In this work we propose a Bayesian approach to causal induction which allows modeling beliefs over multiple causal hypotheses and predicting the behavior of the world under causal interventions. We then illustrate how this method extracts causal information from data containing interventions and observations.