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National audience; In real world scenarios, the formation of consensus is an self-organisation process by which actors have to make a joint assessment about a target subject being it a decision making problem or the formation of a collective opinion. In social simulation, models of opinion dynamics tackle the opinion formation phenomena. These models try to make an assessment, for instance, of the ideal conditions that lead an interacting group of agents to opinion consensus, polarisation or fragmentation. In this paper, we investigate the role of social relation structure in opinion dynamics using an interaction model of relative agreement. We present an agent-based model that defines social relations as multiple concomitant social networks and apply our model to an opinion dynamics model with bounded confidence. We discuss the influence of complex social network topologies where actors interact in multiple relations simultaneously. The paper builds on previous work about social space design with multiple contexts and context switching, to determine the influence of such complex social structures in a process such as opinion formation.

International audience; In this paper, we show how a dangerousness metric can be used to modify the input of a gene regulatory network when plugged to a virtual car. In the context of the 2015 Simulated Car Racing Championship organized during GECCO 2015, we have developed a new cartography methodology able to inform the controller of the car about the incoming complexity of the track: turns (slipperiness, angle, etc.) and bumps. We show how this dangerousness metric improves the results of our controller and outperforms other approaches on the tracks used in the competition.

Recent works about pedestrian simulation can actually be sorted in two categories. The first ones focusing on large crowd simulation aim to solve performance and scalability issues at the expense of behavioral realism of each simulated individual. The second ones aim at individual behavioral realism but the computational cost is too expensive to simulate crowds. In this paper, we propose an alternate approach combining a light reactive behavior with cognitive strategies issued from real life videos. This approach aims at the real time simulation of small crowds of pedestrians (one to two hundred individuals) but with concerns for visual realism regarding heterogeneous behaviors, trajectories and positioning on sidewalks.