Extending Reynolds' Flocking Model to a Simulation of Sheep in The
Total Page:16
File Type:pdf, Size:1020Kb
Load more
Recommended publications
-
Dispersal, Philopatry, and the Role of Fissionfusion Dynamics In
MARINE MAMMAL SCIENCE, **(*): ***–*** (*** 2012) C 2012 by the Society for Marine Mammalogy DOI: 10.1111/j.1748-7692.2011.00559.x Dispersal, philopatry, and the role of fission-fusion dynamics in bottlenose dolphins YI-JIUN JEAN TSAI and JANET MANN,1 Reiss Science Building, Rm 406, Department of Biology, Georgetown University, Washington, DC 20057, U.S.A. ABSTRACT In this quantitative study of locational and social dispersal at the individual level, we show that bottlenose dolphins (Tursiops sp.) continued to use their na- tal home ranges well into adulthood. Despite substantial home range overlap, mother–offspring associations decreased after weaning, particularly for sons. These data provide strong evidence for bisexual locational philopatry and mother–son avoidance in bottlenose dolphins. While bisexual locational philopatry offers the benefits of familiar social networks and foraging habitats, the costs of philopatry may be mitigated by reduced mother–offspring association, in which the risk of mother–daughter resource competition and mother–son mating is reduced. Our study highlights the advantages of high fission–fusion dynamics and longitudinal studies, and emphasizes the need for clarity when describing dispersal in this and other species. Key words: bottlenose dolphin, Tursiops sp., association, juvenile, philopatry, locational dispersal, mother-offspring, ranging, site fidelity, social dispersal. Dispersal is a key life history process that affects population demography, spatial distribution, and genetic structure, as well as individual -
Flocks and Crowds
Flocks and Crowds Flocks and crowds are other essential concepts we'll be exploring in this book. amount of realism to your simulation in just a few lines of code. Crowds can be a bit more complex, but we'll be exploring some of the powerful tools that come bundled with Unity to get the job done. In this chapter, we'll cover the following topics: Learning the history of flocks and herds Understanding the concepts behind flocks Flocking using the Unity concepts Flocking using the traditional algorithm Using realistic crowds the technology being the swarm of bats in Batman Returns in 1992, for which he won an and accurate, the algorithm is also very simple to understand and implement. [ 115 ] Understanding the concepts behind As with them to the real-life behaviors they model. As simple as it sounds, these concepts birds exhibit in nature, where a group of birds follow one another toward a common on the group. We've explored how singular agents can move and make decisions large groups of agents moving in unison while modeling unique movement in each Island. This demo came with Unity in Version 2.0, but has been removed since Unity 3.0. For our project. the way, you'll notice some differences and similarities, but there are three basic the algorithm's introduction in the 80s: Separation: This means to maintain a distance with other neighbors in the flock to avoid collision. The following diagram illustrates this concept: Here, the middle boid is shown moving in a direction away from the rest of the boids, without changing its heading [ 116 ] Alignment: This means to move in the same direction as the flock, and with the same velocity. -
The Influence of Density in Population Dynamics with Strong and Weak Allee Effect
Keya et al. J Egypt Math Soc (2021) 29:4 https://doi.org/10.1186/s42787-021-00114-x Journal of the Egyptian Mathematical Society ORIGINAL RESEARCH Open Access The infuence of density in population dynamics with strong and weak Allee efect Kamrun Nahar Keya1, Md. Kamrujjaman2* and Md. Shafqul Islam3 *Correspondence: [email protected] Abstract 2 Department In this paper, we consider a reaction–difusion model in population dynamics and of Mathematics, University of Dhaka, Dhaka 1000, study the impact of diferent types of Allee efects with logistic growth in the hetero- Bangladesh geneous closed region. For strong Allee efects, usually, species unconditionally die out Full list of author information and an extinction-survival situation occurs when the efect is weak according to the is available at the end of the article resource and sparse functions. In particular, we study the impact of the multiplicative Allee efect in classical difusion when the sparsity is either positive or negative. Nega- tive sparsity implies a weak Allee efect, and the population survives in some domain and diverges otherwise. Positive sparsity gives a strong Allee efect, and the popula- tion extinct without any condition. The infuence of Allee efects on the existence and persistence of positive steady states as well as global bifurcation diagrams is presented. The method of sub-super solutions is used for analyzing equations. The stability condi- tions and the region of positive solutions (multiple solutions may exist) are presented. When the difusion is absent, we consider the model with and without harvesting, which are initial value problems (IVPs) and study the local stability analysis and present bifurcation analysis. -
Swarm Intelligence
Swarm Intelligence Leen-Kiat Soh Computer Science & Engineering University of Nebraska Lincoln, NE 68588-0115 [email protected] http://www.cse.unl.edu/agents Introduction • Swarm intelligence was originally used in the context of cellular robotic systems to describe the self-organization of simple mechanical agents through nearest-neighbor interaction • It was later extended to include “any attempt to design algorithms or distributed problem-solving devices inspired by the collective behavior of social insect colonies and other animal societies” • This includes the behaviors of certain ants, honeybees, wasps, cockroaches, beetles, caterpillars, and termites Introduction 2 • Many aspects of the collective activities of social insects, such as ants, are self-organizing • Complex group behavior emerges from the interactions of individuals who exhibit simple behaviors by themselves: finding food and building a nest • Self-organization come about from interactions based entirely on local information • Local decisions, global coherence • Emergent behaviors, self-organization Videos • https://www.youtube.com/watch?v=dDsmbwOrHJs • https://www.youtube.com/watch?v=QbUPfMXXQIY • https://www.youtube.com/watch?v=M028vafB0l8 Why Not Centralized Approach? • Requires that each agent interacts with every other agent • Do not possess (environmental) obstacle avoidance capabilities • Lead to irregular fragmentation and/or collapse • Unbounded (externally predetermined) forces are used for collision avoidance • Do not possess distributed tracking (or migration) -
Comparative Methods Offer Powerful Insights Into Social Evolution in Bees Sarah Kocher, Robert Paxton
Comparative methods offer powerful insights into social evolution in bees Sarah Kocher, Robert Paxton To cite this version: Sarah Kocher, Robert Paxton. Comparative methods offer powerful insights into social evolution in bees. Apidologie, Springer Verlag, 2014, 45 (3), pp.289-305. 10.1007/s13592-014-0268-3. hal- 01234748 HAL Id: hal-01234748 https://hal.archives-ouvertes.fr/hal-01234748 Submitted on 27 Nov 2015 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. Apidologie (2014) 45:289–305 Review article * INRA, DIB and Springer-Verlag France, 2014 DOI: 10.1007/s13592-014-0268-3 Comparative methods offer powerful insights into social evolution in bees 1 2 Sarah D. KOCHER , Robert J. PAXTON 1Department of Organismic and Evolutionary Biology, Museum of Comparative Zoology, Harvard University, Cambridge, MA, USA 2Institute for Biology, Martin-Luther-University Halle-Wittenberg, Halle, Germany Received 9 September 2013 – Revised 8 December 2013 – Accepted 2 January 2014 Abstract – Bees are excellent models for studying the evolution of sociality. While most species are solitary, many form social groups. The most complex form of social behavior, eusociality, has arisen independently four times within the bees. -
Interactive Robots in Experimental Biology 3 4 5 6 Jens Krause1,2, Alan F.T
1 2 Interactive Robots in Experimental Biology 3 4 5 6 Jens Krause1,2, Alan F.T. Winfield3 & Jean-Louis Deneubourg4 7 8 9 10 11 12 1Leibniz-Institute of Freshwater Ecology and Inland Fisheries, Department of Biology and 13 Ecology of Fishes, 12587 Berlin, Germany; 14 2Humboldt-University of Berlin, Department for Crop and Animal Sciences, Philippstrasse 15 13, 10115 Berlin, Germany; 16 3Bristol Robotics Laboratory, University of the West of England, Coldharbour Lane, Bristol 17 BS16 1QY, UK; 18 4Unit of Social Ecology, Campus Plaine - CP 231, Université libre de Bruxelles, Bd du 19 Triomphe, B-1050 Brussels - Belgium 20 21 22 23 24 25 26 27 28 Corresponding author: Krause, J. ([email protected]), Leibniz Institute of Freshwater 29 Ecology and Inland Fisheries, Department of the Biology and Ecology of Fishes, 30 Müggelseedamm 310, 12587 Berlin, Germany. 31 32 33 1 33 Interactive robots have the potential to revolutionise the study of social behaviour because 34 they provide a number of methodological advances. In interactions with live animals the 35 behaviour of robots can be standardised, morphology and behaviour can be decoupled (so that 36 different morphologies and behavioural strategies can be combined), behaviour can be 37 manipulated in complex interaction sequences and models of behaviour can be embodied by 38 the robot and thereby be tested. Furthermore, robots can be used as demonstrators in 39 experiments on social learning. The opportunities that robots create for new experimental 40 approaches have far-reaching consequences for research in fields such as mate choice, 41 cooperation, social learning, personality studies and collective behaviour. -
Breeding Site Fidelity in Southern Elephant Seals of the Falkland Islands
Filippo Galimberti 1 and Simona Sanvito 1,2 1 Elephant Seal Research Group, Sea Lion Island, Falkland Islands 2 Dept. of Biology, Memorial University of Newfoundland, St. John’s NF A1B 3X9, Canada ESRG technical report no. 3 Breeding site fidelity in southern elephant seals of the Falkland Islands Milano, 25th April 2000 © Elephant Seal Research Group – 2000 No part of this report can be cited without written permission from the authors. Address for correspondence: Dr. Filippo Galimberti – Via Buonarroti 35 – 20145 Milano – Italy Phone +39 02 4980504 – Fax +39 02 48008145 – Email [email protected] ABSTRACT Breeding site fidelity, i.e., the tendency to return to the same breeding site for consecutive breeding attempts, is an important component of mammal life history strategies, and seems almost ubiquitous in Pinnipedia species, at least for land breeding ones. Site fidelity may entail significant somatic benefits and costs, and, if coupled with return for first breeding attempt to birth site, may produce a genetic sub-structuring of populations. We present data on female and male site fidelity, together with preliminary information on female phylopatry, of southern elephant seals (Mirounga leonina) of Sea Lion Island, the main breeding site of the species in the Falkland Islands. We found a high level of site fidelity at small scale (hundred of metres) in both sexes, although higher in females, even when considering up to five consecutive breeding seasons of the same individual. We discuss the behavioural and genetic implications of site fidelity, emphasizing that it may affect mating tactics, breeding success, and genetic sub-structuring of local populations. -
Counter-Misdirection in Behavior-Based Multi-Robot Teams *
Counter-Misdirection in Behavior-based Multi-robot Teams * Shengkang Chen, Graduate Student Member, IEEE and Ronald C. Arkin, Fellow, IEEE Abstract—When teams of mobile robots are tasked with misdirection approach using a novel type of behavior-based different goals in a competitive environment, misdirection and robot agents: counter-misdirection agents (CMAs). counter-misdirection can provide significant advantages. Researchers have studied different misdirection methods but the II. BACKGROUND number of approaches on counter-misdirection for multi-robot A. Robot Deception systems is still limited. In this work, a novel counter-misdirection approach for behavior-based multi-robot teams is developed by Robotic deception can be interpreted as robots using deploying a new type of agent: counter misdirection agents motions and communication to convey false information or (CMAs). These agents can detect the misdirection process and conceal true information [4],[5]. Deceptive behaviors can have “push back” the misdirected agents collaboratively to stop the a wide range of applications from military [6] to sports [7]. misdirection process. This approach has been implemented not only in simulation for various conditions, but also on a physical Researchers have studied robotic deception previously [4] robotic testbed to study its effectiveness. It shows that this through computational approaches [8] in a wide range of areas approach can stop the misdirection process effectively with a from human–robot interaction (HRI) [9]–[11] to ethical issues sufficient number of CMAs. This novel counter-misdirection [4]. Shim and Arkin [5] proposed a taxonomy of robot approach can potentially be applied to different competitive deception with three basic dimensions: interaction object, scenarios such as military and sports applications. -
Boids Algorithm in Economics and Finance a Lesson from Computational Biology
University of Amsterdam Faculty of Economics and Business Master's thesis Boids Algorithm in Economics and Finance A Lesson from Computational Biology Author: Pavel Dvoˇr´ak Supervisor: Cars Hommes Second reader: Isabelle Salle Academic Year: 2013/2014 Declaration of Authorship The author hereby declares that he compiled this thesis independently, using only the listed resources and literature. The author also declares that he has not used this thesis to acquire another academic degree. The author grants permission to University of Amsterdam to reproduce and to distribute copies of this thesis document in whole or in part. Amsterdam, July 18, 2014 Signature Bibliographic entry Dvorˇak´ , P. (2014): \Boids Algorithm in Economics and Finance: A Les- son from Computational Biology." (Unpublished master's thesis). Uni- versity of Amsterdam. Supervisor: Cars Hommes. Abstract The main objective of this thesis is to introduce an ABM that would contribute to the existing ABM literature on modelling expectations and decision making of economic agents. We propose three different models that are based on the boids model, which was originally designed in biology to model flocking be- haviour of birds. We measure the performance of our models by their ability to replicate selected stylized facts of the financial markets, especially those of the stock returns: no autocorrelation, fat tails and negative skewness, non- Gaussian distribution, volatility clustering, and long-range dependence of the returns. We conclude that our boids-derived models can replicate most of the listed stylized facts but, in some cases, are more complicated than other peer ABMs. Nevertheless, the flexibility and spatial dimension of the boids model can be advantageous in economic modelling in other fields, namely in ecological or urban economics. -
Animating Predator and Prey Fish Interactions
Georgia State University ScholarWorks @ Georgia State University Computer Science Dissertations Department of Computer Science 5-6-2019 Animating Predator and Prey Fish Interactions Sahithi Podila Follow this and additional works at: https://scholarworks.gsu.edu/cs_diss Recommended Citation Podila, Sahithi, "Animating Predator and Prey Fish Interactions." Dissertation, Georgia State University, 2019. https://scholarworks.gsu.edu/cs_diss/149 This Dissertation is brought to you for free and open access by the Department of Computer Science at ScholarWorks @ Georgia State University. It has been accepted for inclusion in Computer Science Dissertations by an authorized administrator of ScholarWorks @ Georgia State University. For more information, please contact [email protected]. ANIMATING PREDATOR AND PREY FISH INTERACTIONS by SAHITHI PODILA Under the Direction of Ying Zhu, PhD ABSTRACT Schooling behavior is one of the most salient social and group activities among fish. They form schools for social reasons like foraging, mating and escaping from predators. Animating a school of fish is difficult because they are large in number, often swim in distinctive patterns that is they take the shape of long thin lines, squares, ovals or amoeboid and exhibit complex coordinated patterns especially when they are attacked by a predator. Previous work in computer graphics has not provided satisfactory models to simulate the many distinctive interactions between a school of prey fish and their predator, how does a predator pick its target? and how does a school of fish react to such attacks? This dissertation presents a method to simulate interactions between prey fish and predator fish in the 3D world based on the biological research findings. -
Flocks, Herds, and Schools: a Distributed Behavioral Model 1
Published in Computer Graphics, 21(4), July 1987, pp. 25-34. (ACM SIGGRAPH '87 Conference Proceedings, Anaheim, California, July 1987.) Flocks, Herds, and Schools: A Distributed Behavioral Model 1 Craig W. Reynolds Symbolics Graphics Division [obsolete addresses removed 2] Abstract The aggregate motion of a flock of birds, a herd of land animals, or a school of fish is a beautiful and familiar part of the natural world. But this type of complex motion is rarely seen in computer animation. This paper explores an approach based on simulation as an alternative to scripting the paths of each bird individually. The simulated flock is an elaboration of a particle system, with the simulated birds being the particles. The aggregate motion of the simulated flock is created by a distributed behavioral model much like that at work in a natural flock; the birds choose their own course. Each simulated bird is implemented as an independent actor that navigates according to its local perception of the dynamic environment, the laws of simulated physics that rule its motion, and a set of behaviors programmed into it by the "animator." The aggregate motion of the simulated flock is the result of the dense interaction of the relatively simple behaviors of the individual simulated birds. Categories and Subject Descriptors: 1.2.10 [Artificial Intelligence]: Vision and Scene Understanding; 1.3.5 [Computer Graphics]: Computational Geometry and Object Modeling; 1.3.7 [Computer Graphics]: Three Dimensional Graphics and Realism-Animation: 1.6.3 [Simulation and Modeling]: Applications. General Terms: Algorithms, design.b Additional Key Words, and Phrases: flock, herd, school, bird, fish, aggregate motion, particle system, actor, flight, behavioral animation, constraints, path planning. -
Expert Assessment of Stigmergy: a Report for the Department of National Defence
Expert Assessment of Stigmergy: A Report for the Department of National Defence Contract No. W7714-040899/003/SV File No. 011 sv.W7714-040899 Client Reference No.: W7714-4-0899 Requisition No. W7714-040899 Contact Info. Tony White Associate Professor School of Computer Science Room 5302 Herzberg Building Carleton University 1125 Colonel By Drive Ottawa, Ontario K1S 5B6 (Office) 613-520-2600 x2208 (Cell) 613-612-2708 [email protected] http://www.scs.carleton.ca/~arpwhite Expert Assessment of Stigmergy Abstract This report describes the current state of research in the area known as Swarm Intelligence. Swarm Intelligence relies upon stigmergic principles in order to solve complex problems using only simple agents. Swarm Intelligence has been receiving increasing attention over the last 10 years as a result of the acknowledgement of the success of social insect systems in solving complex problems without the need for central control or global information. In swarm- based problem solving, a solution emerges as a result of the collective action of the members of the swarm, often using principles of communication known as stigmergy. The individual behaviours of swarm members do not indicate the nature of the emergent collective behaviour and the solution process is generally very robust to the loss of individual swarm members. This report describes the general principles for swarm-based problem solving, the way in which stigmergy is employed, and presents a number of high level algorithms that have proven utility in solving hard optimization and control problems. Useful tools for the modelling and investigation of swarm-based systems are then briefly described.