Probabilistic aggregation is a self-organised behaviour studied in swarm robotics. It aims at gathering a population of robots in the same place, in order to favour the execution of other more complex collective behaviours or tasks. However, probabilistic aggregation is extremely sensitive to experimental conditions, and thus requires specific parameter tuning for different conditions such as population size or density. To tackle this challenge, in this paper, we present a novel embodied evolution approach for swarm robotics based on social dynamics. This idea hinges on the cultural evolution metaphor, which postulates that good ideas spread widely in a population. Thus, we propose that good parameter settings can spread following a social dynamics process. Testing this idea on probabilistic aggregation and using the minimal naming game to emulate social dynamics, we observe a significant improvement in the scalability of the aggregation process.

Abstract:A comparison between a traditional packed column and a novel membrane contactor used for CO 2 absorption with carbonate production is addressed in this paper. Membrane technology is generally characterized by a lower energy consumption, it offers an independent control of gas and liquid streams, a known interfacial area and avoids solvent dragging. Those advantages make it a potential substitute of conventional absorption towers. The effect of the concentration and the flow rates of both the flue gas (10-15% of CO 2 ) and the alkaline sorbent (NaOH, NaOH/Na 2 CO 3 ) on the variation of the species present in the system, the mass transfer coefficient, and the CO 2 removal efficiency was evaluated. Under the studied operation conditions, the membrane contactor showed very competitive results with the conventional absorption column, even though the highest mass transfer coefficient was found in the latter technology. In addition, the membrane contactor offers an intensification factor higher than five due to its compactness and modular character.

While direct local communication is very important for the organization of robot swarms, so far it has mostly been used for relatively simple tasks such as signaling robots preferences or states. Inspired by the emergence of meaning found in natural languages, more complex communication skills could allow robot swarms to tackle novel situations in ways that may not be a priori obvious to the experimenter. This would pave the way for the design of robot swarms with higher autonomy and adaptivity. The state of the art regarding the emergence of communication for robot swarms has mostly focused on offline evolutionary approaches, which showed that signaling and communication can emerge spontaneously even when not explicitly promoted. However, these approaches do not lead to complex, language-like communication skills, and signals are tightly linked to environmental and/or sensory-motor states that are specific to the task for which communication was evolved. To move beyond current practice, we advocate an approach to emergent communication in robot swarms based on language games. Thanks to language games, previous studies showed that cultural self-organization-rather than biological evolution-can be responsible for the complexity and expressive power of language. We suggest that swarm robotics can be an ideal test-bed to advance research on the emergence of language-like communication. The latter can be key to provide robot swarms with additional skills to support self-organization and adaptivity, enabling the design of more complex collective behaviors.

In this paper, we study a swarm of robots that has to select one aggregation site in an environment in which two sites are available. It is known in the literature that, in presence of asymmetries in the environment, robot swarms are able to perform a collective choice and aggregate in one among two possible sites, for example the largest of the two. We focus on an aggregation scenario where the environment is morphologically symmetric. The two aggregation sites are identical with only one exception: their colour. In addition, in the swarm only a proportion of robots, that we call the informed robots, possess extra information concerning on which specific site the swarm is required to aggregate. The rest of the robots are non-informed, thus they do not possess the above mentioned extra information. In simulation-based experiments we show that, if no robot in the swarm is informed, the swarm is able to break the symmetry and aggregates on one of the two sites at random. However, the introduction of a small proportion of informed robots is enough to break the symmetry: the majority of the swarm aggregates on the site preferred by the informed robot. Additionally, the swarm is also able to completely aggregate on one of the two sites when only half the robots are informed, independently from the swarm size among those we considered. Finally, we analyse how the time dynamics of the aggregation process depend on the proportion of informed robots.

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