Reallocation Problems in Agent Societies: A Local Mechanism to Maximize Social Welfare

Resource reallocation problems are common in real life and therefore gain an increasing interest in Computer Science and Economics. Such problems consider agents living in a society and negotiating their resources with each other in order to improve the welfare of the population. In many studies however, the unrealistic context considered, where agents have a flawless knowledge and unlimited interaction abilities, impedes the application of these techniques in real life problematics. In this paper, we study how agents should behave in order to maximize the welfare of the society. We propose a multi-agent method based on autonomous agents endowed with a local knowledge and local interactions. Our approach features a more realistic environment based on social networks, inside which we provide the behavior for the agents and the negotiation settings required for them to lead the negotiation processes towards socially optimal allocations. We prove that bilateral transactions of restricted cardinality are sufficient in practice to converge towards an optimal solution for different social objectives. An experimental study supports our claims and highlights the impact of a realistic environment on the efficiency of the techniques utilized.Resource Allocation, Negotiation, Social Welfare, Agent Society, Behavior, Emergence

Epireflective subcategories and formal closure operators

On a category $\mathscr{C}$ with a designated (well-behaved) class $\mathcal{M}$ of monomorphisms, a closure operator in the sense of D. Dikranjan and E. Giuli is a pointed endofunctor of $\mathcal{M}$, seen as a full subcategory of the arrow-category $\mathscr{C}^\mathbf{2}$ whose objects are morphisms from the class $\mathcal{M}$, which "commutes" with the codomain functor $\mathsf{cod}\colon \mathcal{M}\to \mathscr{C}$. In other words, a closure operator consists of a functor $C\colon \mathcal{M}\to\mathcal{M}$ and a natural transformation $c\colon 1_\mathcal{M}\to C$ such that $\mathsf{cod} \cdot C=C$ and $\mathsf{cod}\cdot c=1_\mathsf{cod}$. In this paper we adapt this notion to the domain functor $\mathsf{dom}\colon \mathcal{E}\to\mathscr{C}$, where $\mathcal{E}$ is a class of epimorphisms in $\mathscr{C}$, and show that such closure operators can be used to classify $\mathcal{E}$-epireflective subcategories of $\mathscr{C}$, provided $\mathcal{E}$ is closed under composition and contains isomorphisms. Specializing to the case when $\mathcal{E}$ is the class of regular epimorphisms in a regular category, we obtain known characterizations of regular-epireflective subcategories of general and various special types of regular categories, appearing in the works of the second author and his coauthors. These results show the interest in investigating further the notion of a closure operator relative to a general functor. They also point out new links between epireflective subcategories arising in algebra, the theory of fibrations, and the theory of categorical closure operators.Comment: 18 pages. Updated version with many improvement

Blind Source Separation with Optimal Transport Non-negative Matrix Factorization

Optimal transport as a loss for machine learning optimization problems has recently gained a lot of attention. Building upon recent advances in computational optimal transport, we develop an optimal transport non-negative matrix factorization (NMF) algorithm for supervised speech blind source separation (BSS). Optimal transport allows us to design and leverage a cost between short-time Fourier transform (STFT) spectrogram frequencies, which takes into account how humans perceive sound. We give empirical evidence that using our proposed optimal transport NMF leads to perceptually better results than Euclidean NMF, for both isolated voice reconstruction and BSS tasks. Finally, we demonstrate how to use optimal transport for cross domain sound processing tasks, where frequencies represented in the input spectrograms may be different from one spectrogram to another.Comment: 22 pages, 7 figures, 2 additional file

Méthodes et outils pour la lexicographie bilingue en ligne : le cas du Grand Dictionnaire Estonien-Français

International audienceLe projet de construction du Grand dictionnaire estonien-français (GDEF), du fait de sa spécificité--une équipe rédactionnelle dispersée--, a immédiatement ressenti la nécessité d'utiliser des méthodes informatiques innovantes permettant le travail à distance et en réseau. Les initiateurs de ce projet ont donc tout naturellement décidé d'utiliser une plate-forme générique de construction de dictionnaires en ligne : la plate-forme Jibiki, fruit de recherches en lexicographie computationnelle. Après avoir exposé les conditions générales dans lesquelles s'inscrit ce projet de lexicographie bilingue en ligne (nécessité d'un tel dictionnaire, travail à distance, structure complexe, bases de données lexicales utilisées), l'article explique les méthodes de travail mises en œuvre dans cecadre (protocole de rédaction en trois étapes) et les solutions informatiques qui les rendent possibles (interface de rédaction en ligne, gestion des contributions, import-export de données, outils annexes)

Russia’s growth problem. Bruegel Policy Contribution Issue n˚4 | February 2019

Between 2014 and 2016, the Russian economy suffered from a currency crisis caused by the collapse of oil prices and the country’s engagement in the conflict with Ukraine. Although the crisis was overcome in the second half of 2016 thanks to prudent fiscal and monetary policies and higher oil prices, economic recovery remains weak and Russia’s medium-term growth prospects look rather disappointing. The weak growth prospects are caused by several factors including: (i) adverse demographic trends – a declining working-age population and ageing of the population; (ii) a poor business and investment climate; (iii) difficulty in diversifying away from the dominant role of the hydrocarbon sector; (iv) Western sanctions on Russia in response to the annexation of Crimea and Russian support for separatists in the eastern Ukraine Donbas region, and Russian countersanctions. To increase potential growth, Russia needs comprehensive economic and institutional reforms that, in turn, will be conditioned by political reforms and by improved economic and political relationships with the United States, the European Union and Russia’s neighbours