The Proceduralization of Hominin Knapping Skill: Memorizing Different Lithic Technologies

Reconstructing the technical and cognitive abilities of past hominins requires an understanding of how skills like stone toolmaking were learned and transmitted. We ask how much of the variability in the uptake of knapping skill is due to the characteristics of the knapping sequences themselves? Fundamental to skill acquisition is proceduralization, the process whereby skilful tasks are converted from declarative memories (consciously memorized facts and events) into procedural memories (sub-consciously memorized actions) via repetitive practice. From knapping footage, we time and encode each action involved in discoidal, handaxe, Levallois and prismatic blade production. The structure and complexity of these reduction sequences were quantified using k-mer analysis and Markov chains. The amount of time spent on tasks and the pattern of core rotations revealed portions of these reduction sequences that are predisposed to being converted into procedural memories. We observed two major pathways to achieve this proceduralization: either a repetitive or a predictable sequence of core rotations. Later Acheulean handaxes and Levallois knapping involved a predictable platform selection sequence, while prismatic blade knapping involved a repetitive exploitation of platforms. Technologies and the portions of their reduction sequence that lend themselves to proceduralization probably facilitated the more rapid uptake of stone toolmaking skill

Stone toolmaking difficulty and the evolution of hominin technological skills

Stone tools are a manifestation of the complex cognitive and dexterous skills of our hominin ancestors. As such, much research has been devoted to understanding the skill requirements of individual lithic technologies. Yet, comparing skill across different technologies, and thus across the vast timespan of the Palaeolithic, is an elusive goal. We seek to quantify a series of commensurable metrics of knapping skill across four different lithic technologies (discoids, handaxes, Levallois, and prismatic blades). To compare the requisite dexterity, coordination, and care involved in each technology, we analysed video footage and lithic material from a series of replicative knapping experiments to quantify deliberation (strike time), precision (platform area), intricacy (flake size relative to core size), and success (relative blank length). According to these four metrics, discoidal knapping appears to be easiest among the sample. Levallois knapping involved an intricate reduction sequence, but did not require as much motor control as handaxes and especially prismatic blades. Compared with the other Palaeolithic technologies, we conclude that prismatic blade knapping is set apart by being a skill intensive means of producing numerous standardised elongate end-products

Colloque international « Le cinéma de Bergson : image – affect – mouvement »

Du 16 au 18 mai derniers s’est tenu à l’ENS-Ulm un colloque international « Le cinéma de Bergson : image – affect – mouvement », organisé par Ioulia Podoroga et Élie During, et qui a rassemblé pas moins de quatorze intervenants. Comme Frédéric Worms – directeur des Annales bergsoniennes et de l’édition critique des Œuvres de Bergson aux Presses Universitaires de France – l’a souligné dans son allocution d’ouverture, malgré l’apparition précoce de discours sur le cinéma qui se sont réclamés de..

La question de l’altruisme dans la première réception russe de Nietzsche (Preobrajenski, Lopatine, Grot, Astafiev)

Le premier débat russe consacré à part entière à Nietzsche a lieu dans les pages de la revue Voprosy filosofii i psikhologii (Questions de philosophie et de psychologie). Le débat prend la forme d’un exposé plutôt enthousiaste, dans le numéro 15 (1892), auquel répondent dans le numéro suivant (1893) trois réquisitoires diversement orientés, mais unanimement critiques. Il porte sur la question morale de l’altruisme. La publication du prem..

Complex discourse units and their semantics

International audienc

A SIMPLE METHOD TO CALIBRATE KINEMATICAL INVARIANTS: APPLICATION TO OVERHEAD THROWING

The aim of this paper is to present a simple calibration method aimed at optimizing the kinematical invariants of a whole body motion capture model, meaning limb lengths and some of the marker placements. A case study and preliminary results are presented and give encouraging insights about the generalized use of such a method in motion analysis in sports

Sharp error bounds for complex floating-point inversion

International audienceWe study the accuracy of the classic algorithm for inverting a complex number given by its real and imaginary parts as floating-point numbers. Our analyses are done in binary floating-point arithmetic, with an unbounded exponent range and in precision $p$; we also assume that the basic arithmetic operations ($+$, $-$, $\times$, $/$) are rounded to nearest, so that the roundoff unit is $u = 2^{-p}$. We bound the largest relative error in the computed inverse either in the componentwise or in the normwise sense. We prove the componentwise relative error bound $3u$ for the complex inversion algorithm (assuming $p \ge 4$), and we show that this bound is asymptotically optimal (as $p\to \infty$) when $p$ is even, and sharp when using one of the basic IEEE 754 binary formats with an odd precision ($p=53,113$). This componentwise bound obviously leads to the same bound $3u$ for the normwise relative error. However, we prove that the smaller bound $2.707131u$ holds (assuming $p \ge 24$) for the normwise relative error, and we illustrate the sharpness of this bound for the basic IEEE 754 binary formats ($p=24, 53, 113$) using numerical examples

A Library for Symbolic Floating-Point Arithmetic

To analyze a priori the accuracy of an algorithm in oating-point arithmetic, one usually derives a uniform error bound on the output, valid for most inputs and parametrized by the precision p. To show further that this bound is sharp, a common way is to build an input example for which the error committed by the algorithm comes close to that bound, or even attains it. Such inputs may be given as oating-point numbers in one of the IEEE standard formats (say, for p = 53) or, more generally, as expressions parametrized by p, that can be viewed as symbolic oating-point numbers. With such inputs, a sharpness result can thus be established for virtually all reasonable formats instead of just one of them. This, however, requires the ability to run the algorithm on those inputs and, in particular, to compute the correctly-rounded sum, product, or ratio of two symbolic oating-point numbers. The goal of this paper is to show how these basic arithmetic operations can be performed automatically. We introduce a way to model symbolic oating-point data, and present algorithms for round-to-nearest addition, multiplication, fused multiply-add, and division. An implementation as a Maple library is also described, and experiments using examples from the literature are provided to illustrate its interest in practice

Linearly bounded infinite graphs

Linearly bounded Turing machines have been mainly studied as acceptors for context-sensitive languages. We define a natural class of infinite automata representing their observable computational behavior, called linearly bounded graphs. These automata naturally accept the same languages as the linearly bounded machines defining them. We present some of their structural properties as well as alternative characterizations in terms of rewriting systems and context-sensitive transductions. Finally, we compare these graphs to rational graphs, which are another class of automata accepting the context-sensitive languages, and prove that in the bounded-degree case, rational graphs are a strict sub-class of linearly bounded graphs