Flock of Robots with Self-Cooperation for Prey-Predator Task

Ordaz-Rivas, Erick; Rodríguez-Liñán, Angel; Torres-Treviño, Luis M.

doi:10.1007/s10846-020-01283-0

Cited by 8 publications

(5 citation statements)

References 50 publications

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“…Most of these works use global information about the position of the sheep swarm and also rely on a single shepherd or a single sheep/item of prey [13][14][15][16]. That limits the real applicability of the behaviors obtained or even the possibility of effectively parallelizing this task.…”

Section: Literature Reviewmentioning

confidence: 99%

Obtaining emergent behaviors for swarm robotics singling with deep reinforcement learning

et al. 2023

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Isolating (singling) an individual from a group can be essential for protection, rescue or capture tasks. In this paper a system with multiple shepherds who must coordinate the sheep to achieve a specific singleness is proposed. We present a realistically modeled system that will be finally tested in a real robotic system. We want to encourage the adaptability of the system and provide different solutions by promoting the emergence of the swarm. In this line we will focus on the use of reinforcement learning, avoiding a manual design of the behavior in order to not restrict the resulting behaviors and to facilitate their adaptation. A detailed MDP model will be specified as well as the keys to reduce its dimensionality and facilitate its training.We will check the results of the obtained singling policy with respect to a greedy policy and focus on evaluating different behavioral strategies that can solve the problem in different ways. In addition, one of the obtained policies will be analyzed in detail to check both its robustness and its scalability with respect to the number of shepherds and sheep. This policy will be finally tested on a physical robotic swarm.

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Section: Literature Reviewmentioning

confidence: 99%

Obtaining emergent behaviors for swarm robotics singling with deep reinforcement learning

et al. 2023

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“…In this sense, the animal group can be described as an active matter system [17–19]. Particular examples include flocking and schooling behavior of biological systems which can be reproduced in computer simulations [20–22], experiments with active colloids [16, 23, 24], as well as robotic swarms [25, 26]. Within the framework of a system comprised of many agents, or particles in the case of physical systems, the macroscopic behavior of the system can be controlled externally.…”

Section: Introductionmentioning

confidence: 99%

“…In this sense, the animal group can be described as an active matter system [17][18][19]. Particular examples include flocking and schooling behavior of biological systems which can be reproduced in computer simulations [20][21][22], experiments with active colloids [16,23,24], as well as robotic swarms [25,26].…”

Section: Introductionmentioning

confidence: 99%

Tuning Collective Behaviour in Zebrafish with Genetic Modification

Yang,

Kawafi,

Tong

et al. 2024

Preprint

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Zebrafish collective behaviour is widely used to assess their physical and mental state, serving as a valuable tool to assess the impact of ageing, disease genetics, and the effect of drugs. The essence of these macroscopic phenomena can be represented by active matter models, where the individuals are abstracted as interactive self-propelling agents. The behaviour of these agents depends on a set of parameters in a manner reminiscent of those between the constituents of physical systems. In a few cases, the system may be controlled at the level of the individual constituents such as the interactions between colloidal particles, or the enzymatic behaviour of de novo proteins. Usually, however, while the collective behaviour may be influenced by environmental factors, it typically cannot be changed at will. Here, we challenge this scenario in a biological context by genetically modifying zebrafish. We thus demonstrate the potential of genetic modification in the context of controlling the collective behaviour of biological active matter systems at the level of the constituents, rather than externally. In particular, we probe the effect of the lack of col11a2 gene in zebrafish, which causes the early onset of osteoarthritis. The resulting col11a2 -/- zebrafish exhibited compromised vertebral column properties, bent their body less while swimming, and took longer to change their orientations. Surprisingly, a group of 25 mutant fish exhibited more orderly collective motion than the wildtype. We show that the collective behaviour of wildtype and col11a2 zebrafish are captured with a simple active matter model, in which the mutant fish are modelled by self–propelling agents with a higher orientational noise on average. In this way, we demonstrate the possibility of tuning a biological system, changing the state space it occupies when interpreted with a simple active matter model.

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“…Behavioral ecologists have investigated cooperative hunting in species like lions, dolphins, and wolves, as well as implemented robots 1 – 8 . Theoretically, extensive research has focused on learning and co-evolution of strategies of predators and prey 9 – 13 .…”

Section: Introductionmentioning

confidence: 99%

Social dilemma in foraging behavior and evolution of cooperation by learning

Lee,

Chae,

Baek

et al. 2023

Sci Rep

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We consider foraging behaviors in a two-dimensional continuum space and show that a cooperative chasing strategy can emerge in a social dilemma. Predators can use two different chasing strategies: A direct chasing strategy (DCS) and a group chasing strategy (GCS). The DCS is a selfish strategy with which a chaser moves straight toward the nearest prey, and the GCS is a cooperative strategy in the sense that the chaser chooses the chasing direction for the group at a cost of its own speed. A prey flees away from the nearest hazard, either a chaser or the boundary, within its recognition range. We check the capturing activities of each strategy and find a social dilemma between the two strategies because the GCS is more efficient for the group whereas the DCS is better individually. Using a series of numerical simulations, we further show that the cooperative strategy can proliferate when a learning process of nearby successful strategies is introduced.

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Flock of Robots with Self-Cooperation for Prey-Predator Task

Cited by 8 publications

References 50 publications

Obtaining emergent behaviors for swarm robotics singling with deep reinforcement learning

Obtaining emergent behaviors for swarm robotics singling with deep reinforcement learning

Tuning Collective Behaviour in Zebrafish with Genetic Modification

Social dilemma in foraging behavior and evolution of cooperation by learning

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