Aliza T. Sloan, Nancy Aaron Jones, and J. A. Scott Kelso

PNAS 120 (39) e2306732120

How do human beings make sense of their relation to the world and realize their ability to effect change? Applying modern concepts and methods of coordination dynamics, we demonstrate that patterns of movement and coordination in 3 to 4-mo-olds may be used to identify states and behavioral phenotypes of emergent agency. By means of a complete coordinative analysis of baby and mobile motion and their interaction, we show that the emergence of agency can take the form of a punctuated self-organizing process, with meaning found both in movement and stillness.

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A. Reina, R. Zakir, G. De Masi, E. Ferrante.

Communications Physics 6: 236, 2023.

Strongly opinionated minorities can have a dramatic impact on the opinion dynamics of a large population. Two factions of inflexible minorities, polarised into two competing opinions, could lead the entire population to persistent indecision. Equivalently, populations can remain undecided when individuals sporadically change their opinion based on individual information rather than social information. Our analysis compares the cross-inhibition model with the voter model for decisions between equally good alternatives, and with the weighted voter model for decisions among alternatives characterised by different qualities. Here we show that cross-inhibition, contrary to the other two models, is a simple mechanism that allows the population to reach a stable majority for one alternative even in the presence of a relatively high amount of asocial behaviour. The results predicted by the mean-field models are confirmed by experiments with swarms of 100 locally interacting robots. This work suggests an answer to the longstanding question of why inhibitory signals are widespread in natural systems of collective decision making, and, at the same time, it proposes an efficient mechanism for designing resilient swarms of minimalistic robots. Reaching group consensus without a leader can be jeopardized by even a minimal number of self-willed individuals. This study shows that, when individuals use inhibitory signals, a stable consensus is guaranteed, thus suggesting an answer to the longstanding question of why inhibition is widespread in natural systems of collective decision making.

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Arash Sadeghi Amjadi, Cem Bilaloğlu, Ali Emre Turgut, Seongin Na, Erol Şahin, Tomáš Krajník, Farshad Arvin
Adaptive Behavior

Aggregation, the gathering of individuals into a single group as observed in animals such as birds, bees, and amoeba, is known to provide protection against predators or resistance to adverse environmental conditions for the whole. Cue-based aggregation, where environmental cues determine the location of aggregation, is known to be challenging when the swarm density is low. Here, we propose a novel aggregation method applicable to real robots in low-density swarms. Previously, Landmark-Based Aggregation (LBA) method had used odometric dead-reckoning coupled with visual landmarks and yielded better aggregation in low-density swarms. However, the method’s performance was affected adversely by odometry drift, jeopardizing its application in real-world scenarios. In this article, a novel Reinforcement Learning-based Aggregation method, RLA, is proposed to increase aggregation robustness, thus making aggregation possible for real robots in low-density swarm settings. Systematic experiments conducted in a kinematic-based simulator and on real robots have shown that the RLA method yielded larger aggregates, is more robust to odometry noise than the LBA method, and adapts better to environmental changes while not being sensitive to parameter tuning, making it better deployable under real-world conditions.

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Measurement and entanglement both have a “spooky” nonlocal flavor to them. Now physicists are harnessing that nonlocality to probe the spread of quantum information and control it.

Read the full article at: www.quantamagazine.org