Embodied Evolution of Self-organised Aggregation by Cultural Propagation

Cambier, Nicolas; Frémont, Vincent; Trianni, Vito; Ferrante, Eliseo

doi:10.1007/978-3-030-00533-7_29

Cited by 9 publications

(15 citation statements)

References 31 publications

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“…For each experiment, we have three different conditions, in which we varied the swarm size (N). As aggregation performance are heavily influenced by swarm density (Cambier et al, 2018), in this paper we have decided to study scalability with respect to the swarm size by keeping the swarm density constant. Therefore, the diameter of the area as well as the diameters of the aggregation sites are varied in proportion to N. Table 1 reports a summary of all experimental conditions.…”

Section: Methodsmentioning

confidence: 99%

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On self-organised aggregation dynamics in swarms of robots with informed robots

Firat

Ferrante

Gillet

et al. 2020

Neural Comput & Applic

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Aggregation is a process observed in natural systems whereby individuals gather together to form large cluster. Recent studies with cockroaches and robots have shown that relatively simple individual mechanisms can account for how individuals manage to gather on a single shelter when two or more are available in the environment. In this paper, we use simulated swarms of robots to further explore the aggregation dynamics generated by these simple individual mechanisms. Our objective is to study the introduction of "informed robots", and to study how many of these are needed to direct the aggregation process toward a pre-defined site among those available in the environment. Informed robots are members of a group that selectively avoid the site/s where no aggregate should emerge, and stop only on the experimenter predefined site/s for aggregation. We study the aggregation process with informed robots in three different scenarios: two that are morphologically symmetric, whereby the different types of aggregation site are equally represented in the environment; and an asymmetric scenario, whereby the target site has an area that is half the area of the sites that should be avoided. We first show what happens when no robot in the swarm is informed: in symmetric environments, the swarm is able to break the symmetry and aggregates on one of the two 1

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Section: Methodsmentioning

confidence: 99%

“…with b = 2.2. This function was also introduced in (Cambier et al, 2018). A robot that decides to leave the aggregation site based on P leave transitions from state S to state L. Both P stay and P leave are sampled every 20 time steps.…”

Section: The Robots' Controllermentioning

confidence: 99%

On self-organised aggregation dynamics in swarms of robots with informed robots

Firat

Ferrante

Gillet

et al. 2020

Neural Comput & Applic

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“…Each robot is controlled by a probabilistic finite state machine (PFSM, see also Figure 1a), similar to the one employed in [20,2,9,6]. The robots' controller is made of three states: Random Walk (RW), Stay (S), and Leave (L).…”

Section: Methodsmentioning

confidence: 99%

“…with n corresponding to the number of other robots currently stationing on the site that are perceived by the robot currently deciding whether to stop or not; and a = 0.6. This function was first introduced in [6]. It interpolates the probability table considered in classical studies such as [20,9].…”

Section: Methodsmentioning

confidence: 99%

Self-organised Aggregation in Swarms of Robots with Informed Robots

Firat¹,

Ferrante

Cambier

et al. 2018

Theory and Practice of Natural Computing

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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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“…Under specific density conditions, robots split into a controllable quantity of coalitions, each characterized by a different word used as identifier. In Cambier et al ( 2018 ), a further interaction was considered, as the words used within the MNG encode the parameter of the aggregation controller, directly impacting the quality of the self-organized aggregation behavior. As a matter of fact, in the MNG, words supported by highly-connected agents propagate more (Baronchelli, 2011 ).…”

Section: Language Games For Robot Swarmsmentioning

confidence: 99%

Language Evolution in Swarm Robotics: A Perspective

et al. 2020

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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.

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Embodied Evolution of Self-organised Aggregation by Cultural Propagation

Cited by 9 publications

References 31 publications

On self-organised aggregation dynamics in swarms of robots with informed robots

On self-organised aggregation dynamics in swarms of robots with informed robots

Self-organised Aggregation in Swarms of Robots with Informed Robots

Language Evolution in Swarm Robotics: A Perspective

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