¿Pueden pensar las máquinas? Una evaluación del problema de la inteligencia artificial mediante el equilibrio refractivo

Revisión del problema de la filosofía de la Inteligencia Artificial a la vista del Equilibrio refractivo. La revisión del problema se lleva a cabo para mostrar como "¿pueden pensar las máquinas?" sólo se ha evaluado en los terminos humanos. El equilibrio refractivo se plantea como una herramienta para definir conceptos de tal modo que la experiencia y los preceptos se encuentren en equilibrio, para con él construir una definición de pensar que no esté limitada exclusivamente a "pensar tal y como lo hacen los humanos".

Genetic basis of Sjögren's syndrome. How strong is the evidence?

Sjögren's syndrome (SS) is a late-onset chronic autoimmune disease (AID) affecting the exocrine glands, mainly the salivary and lachrymal. Genetic studies on twins with primary SS have not been performed, and only a few case reports describing twins have been published. The prevalence of primary SS in siblings has been estimated to be 0.09% while the reported general prevalence of the disease is approximately 0.1%. The observed aggregation of AIDs in families of patients with primary SS is nevertheless supportive for a genetic component in its etiology. In the absence of chromosomal regions identified by linkage studies, research has focused on candidate gene approaches (by biological plausibility) rather than on positional approaches. Ancestral haplotype 8.1 as well as TNF, IL10 and SSA1 loci have been consistently associated with the disease although they are not specific for SS. In this review, the genetic component of SS is discussed on the basis of three known observations: (a) age at onset and sex-dependent presentation, (b) familial clustering of the disease, and (c) dissection of the genetic component. Since there is no strong evidence for a specific genetic component in SS, a large international and collaborative study would be suitable to assess the genetics of this disorder.

On the exhaustiveness of truncation and dropping strategies in many-to-many matching markets

We consider two–sided many–to–many matching markets in which each worker may work for multiple firms and each firm may hire multiple workers. We study individual and group manipulations in centralized markets that employ (pairwise) stable mechanisms and that require participants to submit rank order lists of agents on the other side of the market. We are interested in simple preference manipulations that have been reported and studied in empirical and theoretical work: truncation strategies, which are the lists obtained by removing a tail of least preferred partners from a preference list, and the more general dropping strategies, which are the lists obtained by only removing partners from a preference list (i.e., no reshuffling). We study when truncation / dropping strategies are exhaustive for a group of agents on the same side of the market, i.e., when each match resulting from preference manipulations can be replicated or improved upon by some truncation / dropping strategies. We prove that for each stable mechanism, truncation strategies are exhaustive for each agent with quota 1 (Theorem 1). We show that this result cannot be extended neither to group manipulations (even when all quotas equal 1 – Example 1), nor to individual manipulations when the agent’s quota is larger than 1 (even when all other agents’ quotas equal 1 – Example 2). Finally, we prove that for each stable mechanism, dropping strategies are exhaustive for each group of agents on the same side of the market (Theorem 2), i.e., independently of the quotas.