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We consider the setting of sequential prediction of arbitrary sequences based on specialized experts. We first provide a review of the relevant literature and present two theoretical contributions: a general analysis of the specialist aggregation rule of Freund et al. (Proceedings of the Twenty-Ninth Annual ACM Symposium on the Theory of Computing (STOC),(More)
When it comes to interpreting others' behaviour, we almost irrepressibly engage in the attribution of mental states (beliefs, emotions…). Such "mentalizing" can become very sophisticated, eventually endowing us with highly adaptive skills such as convincing, teaching or deceiving. Here, sophistication can be captured in terms of the depth of our recursive(More)
We consider the sequential short-term forecast of electricity consumption based on ensemble methods. That is, we use several possibly independent base forecasters and design meta-forecasters which combine the base predictions that are output by them. These meta-forecasters are extracted from the literature of sequential learning, namely, from the field(More)
Mentalizing or Theory of Mind (ToM), i.e., the ability to recognize what people think or feel, is a crucial component of human social intelligence. It has been recently proposed that ToM can be decomposed into automatic and controlled neurocognitive components, where only the latter engage executive functions (e.g., working memory, inhibitory control and(More)
Efficient cognitive decisions should be adjustable to incoming novel information. However, most current models of decision making have so far neglected any potential interaction between intentional and stimulus-driven decisions. We report here behavioral results and a new model on the interaction between a perceptual decision and non-predictable novel(More)
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