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International audience; Products/Components received after being used are of a significant uncertainty and variability when it comes to their quantity and quality levels. A technology with a flexible production, in terms of free processing, able to cope with the challenges of uncertainty in remanufacturing processes is needed. By adding material layer by layer, additive manufacturing (AM) represents a new technology that might have a positive impact on the circular economy strategies. Previous studies reviewed the implications of additive remanufacturing from its technical feasibility and the sustainable viability of such processes. These works did not take into account the characterization and selection of Products/Components able to be remanufactured by additive remanufacturing process. This work will focus on the products/components with characteristics that are adequate with additive remanufacturing. It will also present a framework of additive remanufacturing and the key steps in order to allow the remanufacturer to decide on the re-manufacturability of the products using additive manufacturing technologies. This assessment feedback might improve the design and the manufacturing processes for additive remanufacturing.

In this paper, we investigate the chaotic behavior of a gene regulatory network modeled by four differential equations and seventeen parameters. This network, called $$\mathrm{V}$$ -system, has been designed to couple in a simple way an oscillating system with one having a bistable switch. After having studied it analytically, we exhibit (by a constructive proof) the mechanism responsible of chaos for a general differential system presenting such a coupling. Namely, given a generic one-parameter family of smooth vector fields on $$\mathbb R ^n$$ presenting a Hopf bifurcation, we prove that under an assumption on the Jacobian at the bifurcation point, we can create such a chaotic system by perturbing the parameter thanks to a hysteresis-type dynamics. Finally, we numerically show that the mechanism highlighted previously takes place in the $$\mathrm{V}$$ -system, for a particular set of values of its parameters.

Les ressources du centre de calcul de l'IN2P3 ont été nécessaires pour obtenir certains des résultats présentés dans ce papier.; International audience; MCTS (Monte Carlo Tree Search) is a well-known and efficient process to cover and evaluate a large range of states for combinatorial problems. We choose to study MCTS for the Computer Go problem, which is one of the most challenging problem in the field of Artificial Intelligence. For this game, a single combinatorial approach does not always lead to a reliable evaluation of the game states. In order to enhance MCTS ability to tackle such problems, one can benefit from game specific knowledge in order to increase the accuracy of the game state evaluation. Such a knowledge is not easy to acquire. It is the result of a constructivist learning mechanism based on the experience of the player. That is why we explore the idea to endow the MCTS with a process inspired by constructivist learning, to self-acquire knowledge from playing experience. In this paper, we propose a complementary process for MCTS called BHRF (Background History Reply Forest), which allows to memorize efficient patterns in order to promote their use through the MCTS process. Our experimental results lead to promising results and underline how self-acquired data can be useful for MCTS based algorithms.