From honeybees to robots and back: division of labour based on partitioning social inhibition

Zahadat, Payam; Hahshold, Sibylle; Thenius, Ronald; Crailsheim, Karl; Schmickl, Thomas

doi:10.1088/1748-3190/10/6/066005

Cited by 24 publications

(10 citation statements)

References 38 publications

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“…In technical systems inspired by social animals, namely, swarm robotics and swarm intelligent systems, regulation through a shared limited resource was found to be beneficial. For example, robotic underwater swarms (39–41) can use shared resources to divide labor, multimodular robot interaction is inspired from resource distribution of substances (42), and hormone robotics (43) is based on a simulated substance flow within the body of the robot.…”

Section: Discussionmentioning

confidence: 99%

Integral feedback control is at the core of task allocation and resilience of insect societies

Schmickl

Karsai

2018

Proc. Natl. Acad. Sci. U.S.A.

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SignificanceA key problem for complex systems is achieving resilience through their (often nonlinear) interactions between components. Social insect colonies are natural examples of highly scalable systems that achieve homeostatic self-regulation based on local interactions. We describe a “functional core model” that we identified in three different insect societies (wasps, ants, and honey bees). This core model is based on self-regulation through a shared (limited) substance that works as an information center and as a buffer system simultaneously. This system has several adaptive properties, as it is robust against environmental disturbances and insensitive against parameter changes. Finding such a “common core model” is of high significance in understanding the discrete transitions from individuality to sociality in several animal species through convergent evolution.

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Section: Discussionmentioning

confidence: 99%

Integral feedback control is at the core of task allocation and resilience of insect societies

Schmickl

Karsai

2018

Proc. Natl. Acad. Sci. U.S.A.

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“…In young honeybees (before the forager age) such negative feedback was shown experimentally in [ 84 ], and then modeled algorithmically in [ 85 – 88 ]. Also, short term adaptation of the age-polyethism regime in honeybees was demonstrated in honeybees [ 89 ] yielding a pheromone-based social-inhibition model [ 90 , 91 ]. Such a pheromone-inhibition system shows similarity to the common stomach model because it is based on negative feedback loops in which the shared substance is a pheromone and not a nutrient substance like in the study presented here.…”

Section: Discussionmentioning

confidence: 99%

Resilience of honeybee colonies via common stomach: A model of self-regulation of foraging

Schmickl

Karsai

2017

PLoS ONE

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We propose a new regulation mechanism based on the idea of the “common stomach” to explain several aspects of the resilience and homeostatic regulation of honeybee colonies.This mechanism exploits shared pools of substances (pollen, nectar, workers, brood) that modulate recruitment, abandonment and allocation patterns at the colony-level and enable bees to perform several survival strategies to cope with difficult circumstances: Lack of proteins leads to reduced feeding of young brood, to early capping of old brood and to regaining of already spent proteins through brood cannibalism. We modeled this system by linear interaction terms and mass-action law. To test the predictive power of the model of this regulatory mechanism we compared our model predictions to experimental data of several studies. These comparisons show that the proposed regulation mechanism can explain a variety of colony level behaviors. Detailed analysis of the model revealed that these mechanisms could explain the resilience, stability and self-regulation observed in honeybee colonies. We found that manipulation of material flow and applying sudden perturbations to colony stocks are quickly compensated by a resulting counter-acting shift in task selection. Selective analysis of feedback loops allowed us to discriminate the importance of different feedback loops in self-regulation of honeybee colonies. We stress that a network of simple proximate mechanisms can explain significant colony-level abilities that can also be seen as ultimate reasoning of the evolutionary trajectory of honeybees.

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“…They span from swarm intelligence (Bonabeau et al 1999) initially inspired by behaviors of social insects, via swarm robotics (Dorigo et al 2014;Hamann 2018b), distributed approaches in microeconomics and market-based methods (Clearwater 1996;Deconinck et al 2015;Kurose and Simha 1989). A common subject of interest shared in all these fields of research is resource distribution that includes task distribution and division of labor (Bonabeau et al 1999;Huberman and Hogg 1995;Waldspurger et al 1992;Zahadat et al 2015;Zahadat and Schmickl 2016). Individual agents in a swarm consume or contribute to the shared resource while trying to meet their own private needs.…”

Section: Multi-agent Systemsmentioning

confidence: 99%

“…The interdependencies induced by resource sharing point to the importance of distribution mechanisms in steering the behavior of swarms, e.g., as in microeconomics and market-based control (Clearwater 1996;Kurose and Simha 1989). Similar topics and challenges also appear in the study of task allocation mechanisms and division of labor, e.g., how to distribute agents-the shared limited resource of the system-to handle sets of given tasks (Bonabeau et al 1997;Karsai and Schmickl 2011;Pini et al 2013;Zahadat et al 2015).…”

Section: Multi-agent Systemsmentioning

confidence: 99%

Toward a theory of collective resource distribution: a study of a dynamic morphogenesis controller

Zahadat

Hofstadler

2019

Swarm Intell

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Nature has various approaches to manage the collective distribution of resources. The division of a honeybee colony into subgroups, the formation of ant trails to food sources, and the spread of tree branches to optimize the access to light are some examples of collective decision making for resource distribution. This paper investigates collective distribution via an algorithm named vascular morphogenesis controller (VMC). This algorithm is inspired by plant morphogenesis that is a result of competitions between branches for shared resources, e.g., water and minerals. The algorithm acts on a directed graph and determines its dynamics over time. The nodes of the graph collectively decide on the distribution of a shared resource to propose the places to add or remove new nodes. The resulting dynamical system is adaptive to variations in the structural and environmental conditions. In this paper, the VMC is embodied in a modular physical structure. The structures' modules host the nodes of the VMC graph. They may suggest changes in the morphology over time, and a human can manually implement them into the physical structure. The paper investigates the effects of different parameters of the algorithm on the collective behavior of the system, both through embodied implementations and theory. The investigations have led to a better understanding of various aspects of the VMC and provided new knowledge to facilitate parameter selection for potential applications. Furthermore, the analyses have indicated similarities between the VMC and other types of collective systems, suggesting the potential benefits of viewing those systems from the perspective of resource distribution.

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From honeybees to robots and back: division of labour based on partitioning social inhibition

Cited by 24 publications

References 38 publications

Integral feedback control is at the core of task allocation and resilience of insect societies

Integral feedback control is at the core of task allocation and resilience of insect societies

Resilience of honeybee colonies via common stomach: A model of self-regulation of foraging

Toward a theory of collective resource distribution: a study of a dynamic morphogenesis controller

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