The evolution of opinions in collectives is influenced by, and simultaneously influences, the interaction network. Simple rules like conformity and homophily drive the co-evolution of network and opinions, leading to the emergence of complex collective behaviors. Studying these behaviors gives insight into complex social dynamics, including the formation of echo chambers. This paper highlights how spatial information sources, and network connectivity shape echo chambers. We propose a potential solution to overcome the local trap of echo chambers by leveraging the mobility of agents.

Inter-individual differences are studied in natural systems, such as fish, bees, and humans, as they contribute to the complexity of both individual and collective behaviors. However, individuality in artificial systems, such as robotic swarms, is undervalued or even overlooked. Agent-specific deviations from the norm in swarm robotics are usually understood as mere noise that can be minimized, for example, by calibration. We observe that robots have consistent deviations and argue that awareness and knowledge of these can be exploited to serve a task. We measure heterogeneity in robot swarms caused by individual differences in how robots act, sense, and oscillate. Our use case is Kilobots and we provide example behaviors where the performance of robots varies depending on individual differences. We show a non-intuitive example of phototaxis with Kilobots where the non-calibrated Kilobots show better performance than the calibrated supposedly “ideal” one. We measure the inter-individual variations for heterogeneity in sensing and oscillation, too. We briefly discuss how these variations can enhance the complexity of collective behaviors. We suggest that by recognizing and exploring this new perspective on individuality, and hence diversity, in robotic swarms, we can gain a deeper understanding of these systems and potentially unlock new possibilities for their design and implementation of applications.

This paper proposes an artificial pheromone communication system inspired by social insects. The proposed model is an extension of the previously developed pheromone communication system, COS-_. The new model increases COS-Φ flexibility by adding two new features, namely, diffusion and advection . The proposed system consists of an LCD flat screen that is placed horizontally, overhead digital camera to track mobile robots, which move on the screen, and a computer, which simulates the pheromone behaviour and visualises its spatial distribution on the LCD. To investigate the feasibility of the proposed pheromone system, real microrobots, Colias , were deployed which mimicked insects’ role in tracking the pheromone sources. The results showed that, unlike the COS-Φ, the proposed system can simulate the impact of environmental characteristics, such as temperature, atmospheric pressure or wind, on the spatio-temporal distribution of the pheromone. Thus, the system allows studying behaviours of pheromone-based robotic swarms in various real-world conditions.