• Title/Summary/Keyword: predator-prey systems

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Boids′ Behavioral Modeling based Fuzzy Flocking (퍼지 플로킹 기반의 보이드 행동 모델링)

  • Kwon, Il-Kyoung;Lee, Sang-Yong
    • Journal of the Korean Institute of Intelligent Systems
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    • v.14 no.2
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    • pp.195-200
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    • 2004
  • Computer games use an intelligent method called flocking for boids' group behavioral modeling. Flocking can naturally model group behavioral patterns of unpredictable forms such as birds and fishes using some computer resource. In this paper, we implemented an ecosystem which is composed of predator and prey for group behavioral modeling of real underwater ecosystem. Also fuzzy logic is applied to implement instinct desire of ecosystem elements. As the result, we confirmed that the model can overcome breakdown of ecosystem and model naturally ecosystem behavior.

Bifurcation Analysis of a Spatiotemporal Parasite-host System

  • Baek, Hunki
    • Kyungpook Mathematical Journal
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    • v.60 no.2
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    • pp.335-347
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    • 2020
  • In this paper, we take into account a parasite-host system with reaction-diffusion. Firstly, we derive conditions for Hopf, Turing, and wave bifurcations of the system in the spatial domain by means of linear stability and bifurcation analysis. Secondly, we display numerical simulations in order to investigate Turing pattern formation. In fact, the numerical simulation discloses that typical Turing patterns, such as spotted, spot-stripelike mixtures and stripelike patterns, can be formed. In this study, we show that typical Turing patterns, which are well known in predator-prey systems ([7, 18, 25]), can be observed in a parasite-host system as well.

Co-Evolution of Fuzzy Rules and Membership Functions

  • Jun, Hyo-Byung;Joung, Chi-Sun;Sim, Kwee-Bo
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 1998.06a
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    • pp.601-606
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    • 1998
  • In this paper, we propose a new design method of an optimal fuzzy logic controller using co-evolutionary concept. In general, it is very difficult to find optimal fuzzy rules by experience when the input and/or output variables are going to increase. Futhermore proper fuzzy partitioning is not deterministic ad there is no unique solution. So we propose a co-evolutionary method finding optimal fuzzy rules and proper fuzzy membership functions at the same time. Predator-Prey co-evolution and symbiotic co-evolution algorithms, typical approaching methods to co-evolution, are reviewed, and dynamic fitness landscape associated with co-evolution is explained. Our algorithm is that after constructing two population groups made up of rule base and membership function, by co-evolving these two populations, we find optimal fuzzy logic controller. By applying the propose method to a path planning problem of autonomous mobile robots when moving objects applying the proposed method to a pa h planning problem of autonomous mobile robots when moving objects exist, we show the validity of the proposed method.

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Learning of Emergent Behaviors in Collective Virtual Robots using ANN and Genetic Algorithm

  • Cho, Kyung-Dal
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.4 no.3
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    • pp.327-336
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    • 2004
  • In distributed autonomous mobile robot system, each robot (predator or prey) must behave by itself according to its states and environments, and if necessary, must cooperate with other robots in order to carry out a given task. Therefore it is essential that each robot have both learning and evolution ability to adapt to dynamic environment. This paper proposes a pursuing system utilizing the artificial life concept where virtual robots emulate social behaviors of animals and insects and realize their group behaviors. Each robot contains sensors to perceive other robots in several directions and decides its behavior based on the information obtained by the sensors. In this paper, a neural network is used for behavior decision controller. The input of the neural network is decided by the existence of other robots and the distance to the other robots. The output determines the directions in which the robot moves. The connection weight values of this neural network are encoded as genes, and the fitness individuals are determined using a genetic algorithm. Here, the fitness values imply how much group behaviors fit adequately to the goal and can express group behaviors. The validity of the system is verified through simulation. Besides, in this paper, we could have observed the robots' emergent behaviors during simulation.

Mathematical models for population changes of two interacting species (상호작용하는 두 생물 종의 개체 수 변화에 대한 수학적 모델)

  • Shim, Seong-A
    • Journal for History of Mathematics
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    • v.25 no.1
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    • pp.45-56
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    • 2012
  • Mathematical biology has been recognized its importance recently and widely studied in the fields of mathematics, biology, medical sciences, and immunology. Mathematical ecology is an academic field that studies how populations of biological species change as times flows at specific locations in their habitats. It was the earliest form of the research field of mathematical biology and has been providing its basis. This article deals with various form of interactions between two biological species in a common habitat. Mathematical models of predator-prey type, competitive type, and simbiotic type are investigated.

Cannibalism in the Korean Salamander (Hynobius leechii: Hynobiidae, Caudata, Amphibia) Larvae

  • Park, Shi-Ryong;Jeong, Ji-Young;Park, Dae-Sik
    • Animal cells and systems
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    • v.9 no.1
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    • pp.13-18
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    • 2005
  • Cannibalism plays important roles at the levels of both individual and population. To enhance overall rate of successful survival and reproduction, salamander larvae may have evolved to consume both conspecifics and heterospecifics. Consuming conspecifics could result in decreased inclusive fitness possibly by killing relatives. In several salamander species, discrimination of salamander larval siblings from non-siblings and heterospecifics to avoid such a risk has been reported. To determine whether the Korean salamander larvae consume non-siblings more often than siblings and to analyze prey preferences of the salamander larvae in several different experimental conditions, a series of foraging experiments was conducted in the laboratory. We found that 1) large cannibal larvae preyed on small sibling more often than small non-sibling in a mixed group of sibling and non-sibling, 2) cannibal larvae prefered to consume live, weak, and small larvae to dead, healthy, and large larvae, and 3) cannibal larvae consumed heterospecific tadpoles more often than conspecific nonsibling larvae in a mixed group. In addition, the larval density was positively correlated with the occurrence of spacing behavior, one of the agonistic predator behaviors among salamander larvae.