Adopting a functionalist perspective, we emphasize the interest of considering imitation as a single capacity with two functions: communication and learning. These two functions both imply such capacities as detection of novelty, attraction toward moving stimuli and perception-action coupling. We propose that the main difference between the processes involved in the two functions is that, in the case of learning, the dynamics is internal to the system constituted by an individual whereas in the case of communication, the dynamics concerns the system composed by the perception of one individual coupled with the action of the other.In this paper, we compare the first developmental steps of imitation in three populations: typically developing children, children with autism, and robots. We show evidence of strong correlations between imitating and being imitated in typical infants and low-functioning children with autism. Relying on this evidence, the robotic perspective is to provide a generic architecture able not only to learn via imitation but also to interact as an emerging property of the system constituted by two similar architectures with a different history.

-Practical examples showcase the key role of plant-based lipids in the design of innovative sustainable specialty ingredients. Great diversity in plant origins and chemical transformations leads to great molecular diversity and explains why bio-based lipids are involved in broad ingredient categories such as biodegradable emollients, environmentally friendly surfactants, rheology modifiers and active ingredients. Choosing lipid structure, with varying fatty chain length, saturation level and branching, determines ingredient functionality and usage, as these vary, for instance in the case of surfactants, solubilizing, wetting, foaming and emulsifying properties (oil-in-water or water-in-oil). The lipid structure also impacts the ingredients' final solid or liquid appearance. Now ready-to-use ingredients can be created and we can innovate with cold processable new cosmetic formulation concepts. Perhaps most importantly, optimal selection of lipid structure and composition can also drive consumer benefits in cosmetic ingredients, especially, the final sensory experience (for excipients) and biological efficacy (for active ingredients). Biobased lipids lead to new ingredients with augmented performance and sensoriality.Keywords: ingredient / emollient / surfactant / efficacy / sensoriality Résumé -Des lipides biosourcés à forte valeur ajoutée pour la cosmétique. Cet article vise à illustrer à travers des exemples concrets le rôle clé des lipides biosourcés dans la création d'ingrédients de spécialités innovants et durables. La grande variété des plantes d'origine et la diversité des procédés de transformation chimiques expliquent la large implication des lipides biosourcés dans de nombreuses catégories d'ingrédients : les émollients et tensio-actifs respectueux de l'environnement, les modificateurs de rhéologie, ainsi que les ingrédients actifs. Le choix de la structure lipidique tel que la longueur de la chaîne grasse, son taux de saturation ou son caractère branché joue un rôle décisif dans la fonctionnalité de l'ingrédient et son usage comme, par exemple, en tant que solubilisant, mouillant, moussant ou émulsionnant (huile-dans-eau ou eau-dans-huile) pour les tensioactifs. La structure lipidique influence aussi l'aspect liquide à solide de l'ingrédient et permet ainsi de créer des ingrédients prêts à l'emploi et d'innover avec des concepts de formulation cosmétique à froid. Enfin, et cela est probablement le plus important, une choix judicieux de la structure et de la composition lipidique peut aussi orienter les bénéfices de l'ingrédient pour le consommateur final, en particulier l'expérience sensorielle pour les excipients et l'efficacité biologique pour les ingrédients actifs. Les lipides biosourcés sont à l'origine de nouveaux ingrédients avec toujours plus de performance et de sensorialité.

We address the control of a hybrid energy storage system composed of a lead battery and hydrogen storage. Powered by photovoltaic panels, it feeds a partially islanded building. We aim to minimize building carbon emissions over a long-term period while ensuring that 35% of the building consumption is powered using energy produced on site. To achieve this long-term goal, we propose to learn a control policy as a function of the building and of the storage state using a Deep Reinforcement Learning approach. We reformulate the problem to reduce the action space dimension to one. This highly improves the proposed approach performance. Given the reformulation, we propose a new algorithm, DDPGαrep, using a Deep Deterministic Policy Gradient (DDPG) to learn the policy. Once learned, the storage control is performed using this policy. Simulations show that the higher the hydrogen storage efficiency, the more effective the learning.