Parameter estimation in softmax decision-making models with linear objective functions

With an eye towards human-centered automation, we contribute to the development of a systematic means to infer features of human decision-making from behavioral data. Motivated by the common use of softmax selection in models of human decision-making, we study the maximum likelihood parameter estimation problem for softmax decision-making models with linear objective functions. We present conditions under which the likelihood function is convex. These allow us to provide sufficient conditions for convergence of the resulting maximum likelihood estimator and to construct its asymptotic distribution. In the case of models with nonlinear objective functions, we show how the estimator can be applied by linearizing about a nominal parameter value. We apply the estimator to fit the stochastic UCL (Upper Credible Limit) model of human decision-making to human subject data. We show statistically significant differences in behavior across related, but distinct, tasks.Comment: In pres

Down-Sampling coupled to Elastic Kernel Machines for Efficient Recognition of Isolated Gestures

In the field of gestural action recognition, many studies have focused on dimensionality reduction along the spatial axis, to reduce both the variability of gestural sequences expressed in the reduced space, and the computational complexity of their processing. It is noticeable that very few of these methods have explicitly addressed the dimensionality reduction along the time axis. This is however a major issue with regard to the use of elastic distances characterized by a quadratic complexity. To partially fill this apparent gap, we present in this paper an approach based on temporal down-sampling associated to elastic kernel machine learning. We experimentally show, on two data sets that are widely referenced in the domain of human gesture recognition, and very different in terms of quality of motion capture, that it is possible to significantly reduce the number of skeleton frames while maintaining a good recognition rate. The method proves to give satisfactory results at a level currently reached by state-of-the-art methods on these data sets. The computational complexity reduction makes this approach eligible for real-time applications.Comment: ICPR 2014, International Conference on Pattern Recognition, Stockholm : Sweden (2014

Construire la valeur d’un service énergétique : la trajectoire de l’effacement diffus en France

Cette monographie propose de reconstituer la trajectoire institutionnelle d’une offre innovante, l’agrégation d’effacement des consommateurs non industriels. Cette trajectoire permet de comprendre comment un sujet a priori technique, l’intégration des activités d’effacements dans le marché de gros de l’électricité, a pu devenir un sujet « politique », ce qui a entrainé une grande instabilité institutionnelle. Le basculement du registre « technique » vers le registre « politique » s’est accompagné d’une intervention des autorités politiques dans les activités de régulation, activités a priori prises en charge par une autorité indépendante. Ce basculement provient d’une vaste polémique provoquée par l’entreprise Voltalis, premier acteur présent sur l’activité de l’effacement diffus. Cette polémique a affaibli le raisonnement économique défendu par l’autorité indépendante et donc sa crédibilité. Cette monographie reconstitue les débats politiques, juridiques et techniques qui ont accompagné et suivi cette polémique, ainsi que l’important travail technique et juridique qui a été nécessaire pour stabiliser le cadre de cette activité. Elle s’appuie sur une étude systématique des documents publics produits dans cette période et sur des entretiens avec quelques acteurs impliqués

Satisficing in multi-armed bandit problems

Satisficing is a relaxation of maximizing and allows for less risky decision making in the face of uncertainty. We propose two sets of satisficing objectives for the multi-armed bandit problem, where the objective is to achieve reward-based decision-making performance above a given threshold. We show that these new problems are equivalent to various standard multi-armed bandit problems with maximizing objectives and use the equivalence to find bounds on performance. The different objectives can result in qualitatively different behavior; for example, agents explore their options continually in one case and only a finite number of times in another. For the case of Gaussian rewards we show an additional equivalence between the two sets of satisficing objectives that allows algorithms developed for one set to be applied to the other. We then develop variants of the Upper Credible Limit (UCL) algorithm that solve the problems with satisficing objectives and show that these modified UCL algorithms achieve efficient satisficing performance.Comment: To appear in IEEE Transactions on Automatic Contro

Elliptic solutions of generalized Brans-Dicke gravity with a non-universal coupling

We study a model of the generalized Brans-Dicke gravity presented in both the Jordan and in the Einstein frames, which are conformally related. We show that the scalar field equations in the Einstein frame are reduced to the geodesics equations on the target space of the nonlinear sigma-model. The analytical solutions in elliptical functions are obtained when the conformal couplings are given by reciprocal exponential functions. The behavior of the scale factor in the Jordan frame is studied using numerical computations. For certain parameters the solutions can describe an accelerated expansion. We also derive an analytical approximation in exponential functions.Comment: 24 pages, 3 figures; v2: typos fixed, few remarks and references added; version to appear in EPJ

Managing uncertain reform through " flexible institutions " : Electricity sector liberalization in France

International audienceTaking into account uncertainties in the governance of a liberal economic reform leads to a challenging paradox. Economic reform requires institutional stability, which is guaranteed by the independence of the economic regulation authorities from political influence and by a loyalty to initial institutional commitments and international standards. However, all economic reform includes a degree of uncertainty in its results. This uncertainty can be reduced during the implementation of the reform. Experience may lead national governments or independent regulatory authorities to introduce adjustments. Nevertheless, adjustments are limited by the initial institutional commitments and institutionalized standards. The case of the liberalization of the electricity sector in France illustrates this paradox. By articulating the sociology of science and technology to new institutionalist theory in sociology, this communication develops the concept of “flexible institution” in order to explain how a highly institutionalized economic model, the electricity market, has been adapted to the political and material specificities of the French energy system