Group chase and escape with some fast chasers

Iwama, Takanori; Sato, Masahide

doi:10.1103/physreve.86.067102

Cited by 24 publications

(11 citation statements)

References 16 publications

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“…The process of information gathering can be non-reciprocal and long-ranged, far beyond the range of standard colloidal interactions [43,44]. Various lattice [45][46][47] and off-lattice [48][49][50][51][52][53][54][55] approaches have been employed in simulations and analytical theory to elucidate the emerging properties in systems of cognitive and self-steering objects. Such studies often focus on hunting and predator-prey systems, and consider optimal predation strategies [48].…”

Section: Introductionmentioning

confidence: 99%

Noisy pursuit and pattern formation of self-steering active particles

Goh¹,

Winkler²,

Gompper³

2022

New J. Phys.

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We consider a moving target and an active pursing agent, modeled as an intelligent active Brownian particle capable of sensing the instantaneous target location and adjusting its direction of motion accordingly. An analytical and simulation study in two spatial dimensions reveals that pursuit performance depends on the interplay between self-propulsion, active reorientation, limited maneuverability, and random noise. Noise is found to have two opposing effects: (i) it is necessary to disturb regular, quasi-elliptical orbits around the target, and (ii) slows down pursuit by increasing the traveled distance of the pursuer. For a stationary target, we predict a universal scaling behavior of the mean pursuer-target distance and of the mean first-passage time as a function of $\mathrm{Pe}^2/\Omega$, where the P'eclet number $\mathrm{Pe}$ characterizes the activity and $\Omega$ the maneuverability. Importantly, the scaling variable $\mathrm{Pe}^2/\Omega$ depends implicitly on the level of thermal or active noise. A similar behavior is found for a moving target, but modified by the velocity ratio $\alpha =u_0/v_0$ of target and pursuer velocities $u_0$ and $v_0$, respectively. We also propose a strategy to sort active pursuers according to their motility by circular target trajectories.

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Section: Introductionmentioning

confidence: 99%

Noisy pursuit and pattern formation of self-steering active particles

Goh¹,

Winkler²,

Gompper³

2022

New J. Phys.

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“…We studied the predator-prey dynamics of a single predator hunting a herd of prey on a square lattice with decision-making species. While many predator-prey models deal with collective predation [28,29,30,31,32] or the search for the optimal number of predators given the number of prey [33], we chose a model consisting of one predator and many prey, which is often found in Nature. Solitary hunters such as tigers, bears, or sea turtles often have herd animals as their target.…”

Section: Discussionmentioning

confidence: 99%

A single predator charging a herd of prey: effects of self volume and predator–prey decision-making

Schwarzl¹,

Godec²,

Oshanin³

et al. 2016

J. Phys. A: Math. Theor.

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We study the degree of success of a single predator hunting a herd of prey on a two dimensional square lattice landscape. We explicitly consider the self volume of the prey restraining their dynamics on the lattice. The movement of both predator and prey is chosen to include an intelligent, decision making step based on their respective sighting ranges, the radius in which they can detect the other species (prey cannot recognise each other besides the self volume interaction): after spotting each other the motion of prey and predator turns from a nearest neighbour random walk into direct escape or chase, respectively. We consider a large range of prey densities and sighting ranges and compute the mean first passage time for a predator to catch a prey as well as characterise the effective dynamics of the hunted prey. We find that the prey's sighting range dominates their life expectancy and the predator profits more from a bad eyesight of the prey than from his own good eye sight. We characterise the dynamics in terms of the mean distance between the predator and the nearest prey. It turns out that effectively the dynamics of this distance coordinate can be captured in terms of a simple Ornstein-Uhlenbeck picture. Reducing the many-body problem to a simple two-body problem by imagining predator and nearest prey to be connected by a Hookean bond, all features of the model such as prey density and sighting ranges merge into the effective binding constant. ‡ In the following we use the language of predator-prey systems, keeping in mind the relevance of the model for such cellular systems.

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“…Since then, many modified versions of the group chase and escape model were proposed. The literatures contain a large body of work on how to enhance the catching efficiency, such as adding interaction among pursuers (keep enough space among pursuers) (Saito et al, 2016), adding lazy or fast pursuers (Iwama and Sato, 2012;Masuko et al, 2017), and using a collective chasing strategy (Janosov et al, 2017). The literatures also contain the study of aggregation in group chase and escape.…”

Section: Related Workmentioning

confidence: 99%

“…Pursuit-evasion phenomena is widely observed in nature, an example of which is the interaction between coyotes, elk and wolves in Yellowstone National Park (Ripple and Larsen, 2000;Gese, 2001). Studying this phenomena provides an insight into natural interactions, such as prey escape strategies (Breakwell, 1975;Bhattacharya et al, 2011Bhattacharya et al, , 2014Yang et al, 2014;Zha et al, 2016;Zhang et al, 2019), collective behavior (Neill and Cullen, 1974;Siegfried and Underhill, 1975;Bertram, 1978), catching efficiency for predators (Iwama and Sato, 2012;Saito et al, 2016;Masuko et al, 2017;Janosov et al, 2017) and the optimal number of predators for predation success (Kamimura and Ohira, 2010;Vicsek, 2010). But this approach can also provide elegant solutions for artificial systems, including the design of target trapping by autonomous robots (Antonelli et al, 2007;Huang et al, 2013;Peng et al, 2016;.…”

Section: Introductionmentioning

confidence: 99%

Synchronous intercept strategies for a robotic defense-intrusion game with two defenders

et al. 2020

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We study the defense-intrusion game, in which a single attacker robot tries to reach a stationary target that is protected by two defender robots. We focus on the "synchronous intercept problem", where both robots have to reach the attacker robot synchronously to intercept it. Assume that the attacker robot has the control policy which is based on attraction to the target and repulsion from the defenders, two kinds of synchronous intercept strategies are proposed for the defense-intrusion game, introduced here as Attackeroriented and Neutral-position-oriented. Theoretical analysis and simulation results show that: (1) The two strategies are able to generate different synchronous intercept patterns: contact intercept pattern and stable non-contact intercept pattern, respectively. (2) The contact intercept pattern allows the defender robots to intercept the attacker robot in finite time, while the stable non-contact intercept pattern generates a periodic attractor that prevents the attack robot from reaching the target for infinite time. There is potential to apply the insights obtained into defense-intrusion in real systems, including aircraft escort and the defense of military targets or territorial boundaries.

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Group chase and escape with some fast chasers

Cited by 24 publications

References 16 publications

Noisy pursuit and pattern formation of self-steering active particles

Noisy pursuit and pattern formation of self-steering active particles

A single predator charging a herd of prey: effects of self volume and predator–prey decision-making

Synchronous intercept strategies for a robotic defense-intrusion game with two defenders

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