), a struc-ture of purposes (called the intentional structure), and the state of focus of attention (called the attentional state). The linguistic structure consists of segments of the discourse into which the utter-ances naturally aggregate. The intentional structure captures the discourse

Freebase is a practical, scalable tuple database used to struc-ture general human knowledge. The data in Freebase is collaboratively created, structured, and maintained. Free-base currently contains more than 125,000,000 tuples, more than 4000 types, and more than 7000 properties. Public read

As part of an on-going project to understand the found* tions of Knowledge Representation, we are attempting to characterize a kind of belief that forms a more appropriate basis for Knowledge Representation systems than that cap tured by the usual possible-world formalizations begun by Hintikka

; the source of items used by the computational system of syntax While it is uncontroversial that our knowledge of language includes a list of atomic elements for syntactic composition, the “Lexicalist” position is of course associated with a stronger claim about the source of building blocks for syntax

Abstract Understanding the mechanisms governing and regulating self-organisation in the developing embryo is a key challenge that has puzzled and fascinated scientists for decades. Since its conception in 1952 the Turing model has been a paradigm for pattern formation, motivating numerous

focus in this work is not on whether the infamous knowledge-base algorithm for the construction of write-ahead logging by Ito et al. is optimal, but rather on presenting a novel system for the practical unification of neural networks and architecture (TellingIre). 1

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and the glycolytic flux as the possible regulators of the pattern. To the best of our knowledge, this is the first closed example of Turing pattern formation in a model of a vital step of the cell metabolism, with a built-in mechanism for changing the diffusion length of the reactants, and with parameter values

) The goal of the internship is to investigate this abstract model, and to formulate efficient criteria to decide whether a given abstract Turing machine corresponds to a concrete Turing machine. Knowledge of Computability Theory, in particular of Turing machines, is appreciated. Knowl-edge of Symbolic

selectively secure FE for Turing machines with a-priori bounded input based on indistinguishability obfuscation (STOC 2015), or achieved FE for general Turing machines only based on knowledge-type assumptions such as public-coin differing-inputs obfuscation (TCC 2015). A consequence of our result is the first