Agent-Based Spatial Simulation with NetLogo

Agent-Based Spatial Simulation with NetLogo

Volumn 2, Issue , 2016, Pages 1-222

  Banos, Arnaud ^a   Lang, Christophe ^a   Marilleau, Nicolas ^a  

^a NONE

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTATIONAL METHODS;

AGENT BASED; AGENT-BASED MODEL; APPLETS; NETLOGO; PRACTICAL ORIENTATIONS; SCIENTIFIC COMMUNITY; SPATIAL SIMULATION;

AUTONOMOUS AGENTS;

EID: 85010510274     PISSN: None     EISSN: None     Source Type: Book    
DOI: None     Document Type: Book

References (110)

1. Abouaïssa H., Kubera Y., Morvan G. Dynamic hybrid traffic flow modeling. arXiv preprint, arXiv:1401.6773 2014.
2. Ade P., Aghanim N., Armitage-Caplan C., et al. Planck 2013 results. I. Overview of products and scientific results. arXiv preprint, arXiv:1303.5062 2013.
3. Adleman L.M. Molecular computation of solutions to combinatorial problems. Science November 1994, 266(5187):1021-1024.
4. Adleman L.M. Computing with DNA. Scientific American 1998, 279(8):34-41.
5. Amblard F., Rouchier J., Bommel P. Evaluation et validation de modèles multi-agents. Modélisation et Simulation Multi-Agents 2006, 103-120. Science-Lavoisier, Hermes. F. Amblard, D. Phan (Eds.).
6. Awais M.U., Mueller W., Elsheikh A., et al. Using the HLA for distributed continuous simulations. 2013 8th EUROSIM Congress on Modeling and Simulation 2013, 544-549. IEEE.
7. Axelrod R. The dissemination of culture: a model with local convergence and global polarization. Journal of Conflict Resolution 1997, 41(2):203-226.
8. Bakis H. Les Réseaux et leurs enjeux sociaux 1993, Presses universitaires de France, Paris.
9. Banos A. Simulating pedestrian behavior in complex and dynamic environments: An agent-based perspective. European Handbook of Theoretical and Quantitative Geography 2009, 1-27. FGSE, Lausanne. F. Bavaud, C. Mager (Eds.).
10. Agent-based Spatial Simulation with NetLogo 1 2015, ISTE Press Ltd, London, and Elsevier Ltd, Oxford. A. Banos, C. Lang, N. Marilleau (Eds.).
11. Banos A., Corson N., Gaudou B., et al. The importance of being hybrid for spatial epidemic models: a multi-scale approach. Systems 2015, 3(4):309-329.
12. Banos A., Corson N., Gaudou B., et al. Coupling micro and macro dynamics models on networks: application to disease spread 2016, 19-33.
13. Barabási A.-L., Albert R. Emergence of scaling in random networks. Science 1999, 286(5439):509-512.
14. Bellman R.E. Adaptive Control Processes: A Guided Tour 1961, MIT Press.
15. Beni G., Wang J. Swarm intelligence in cellular robotic systems. Robots and Biological Systems: Towards a New Bionics? 1993, Springer, Berlin Heidelberg. P. Dario, G. Sandini, P. Aebischer (Eds.).
16. Bertho-Lavenir C., Carré P.-A., Guerrier C. Télégraphes et Téléphones: de Valmy au Microprocesseur 1981, Librairie générale française, Paris.
17. Berry G., Boudol G. The chemical abstract machine 1990, 81-94.
18. Bertelle C., Dutot A., Guinand F., et al. Organization detection using emergent computing. International Transactions on Systems Science and Applications 2006, 2(1):61-69.
19. Bergez J., Garcia F., Raynal H. RECORD: an integrated framework to build, evaluate and simulate cropping systems. Agro2010'the XIth ESA Congress 2010, 929-930. Agropolis International Editions, Montpellier.
20. Biada L. Ant cemetery https://flickr.com/photos/pedroscreamerovsky/69115494%2046.
21. Blanchart E., Marilleau N., Chotte J.-L., et al. SWORM: an agent-based model to simulate the effect of earthworms on soil structure. European Journal of Soil Science 2009, 60(1):13-21.
22. Bondy J.A., Murty U.S.R. Graph Theory with Applications 1976, Macmillan.
23. Bonabeau E., Theraulaz G. Auto-organisation et comportements collectifs: La modélisation des sociétés d'insectes. Auto-Organisation et Comportement 1997, 91-140. Hermes Science, Paris. G. Theraulaz, F. Spitz (Eds.).
24. Bonabeau E., Theraulaz G., Deneubourg J.-L., et al. Self-organization in social insects. Trends in Ecology & Evolution 1997, 12(5):188-193.
25. Bonabeau E., Dorigo M., Theraulaz G. Swarm Intelligence, From Natural to Artificial Swarm Intelligence 1999, Oxford University Press.
26. Bouzy B., Cazenave T. Computer go: an AI oriented survey. Artificial Intelligence 2001, 132(33):39-103.
27. Bourrel E. Modélisation dynamique de l'écoulement du trafic routier: du macroscopique au microscopique 2003, University Nice Sophia Antipolis, PhD thesis.
28. Brandes U. A faster algorithm for betweenness centrality. Journal of Mathematical Sociology 2001, 25(2):163-177.
29. Bulle N. Les modèles formels et l'explication en sciences sociales. L'Année Sociologique 2005, 55(1):19.
30. Burghout W., Koutsopoulos H. Hybrid traffic simulation models: vehicle loading at meso-micro boundaries 2006.
31. Clerc M., Kennedy J. The particle swarm - explosion, stability, and convergence in a multidimensional complex space. IEEE Transactions on Evolutionary Computation, IEEE 2002, 6(1):58-73.
32. Colorni A., Dorigo M., Maniezzo V. Distributed optimization by ant colonies 1991, 134-142. vol. 142.
33. Crespi B.J., Yanega D. The definition of eusociality. Behavioral Ecology 1995, 6(1):109-115.
34. Daudé E., Laperrière V., Lemoy R., et al. EpiSim: simulation d'épidémies. Recueil de Fiches Pédagogiques du Réseau MAPS July 2014, 47-68. C. Maps (Ed.).
35. Deb K., Agrawal S., Pratap A., et al. A fast elitist non-dominated sorting genetic algorithm for multi-objective optimization: NSGA-II. Lecture Notes in Computer Science 2000, 1917:849-858.
36. Deneubourg J.-L., Aron S., Goss S., et al. The self-organizing exploratory pattern of the Argentine ant. Journal of Insect Behavior March 1990, 3(2):159-168.
37. Deneubourg J.-L., Goss S., Franks N., et al. The dynamics of collective sorting robot-like ants and ant-like robots 1991, 356-363.
38. Dijkstra E.W. A Short Introduction to the Art of Programming 1971, 4. Technische Hogeschool.
39. Eberhart R., Kennedy J. A new optimizer using particle swarm theory 1995, 39-43. vol. 1.
40. Erdös P., Rényi A. On random graphs. Publicationes Mathematicae Debrecen 1959, 6:290-297.
41. Euler L. Solutio problemata ad geometriam situs pertinentis, Commentarii Academiae Scientiarum Imperialis Petropolitanae. Commentarii Academiae Scientiarum Petropolitanae 1741, 8:128-140. available at. https://math.dartmouth.edu/euler/docs/originals/E053.pdf.
42. Ferber J., Perrot J.-F. Les Systèmes Multi-Agents: Vers une Intelligence Collective 1997, InterEditions, Paris.
43. Forrest S. Emergent Computation 1991, MIT Press.
44. Fortunato S. Community detection in graphs. Physics Reports 2010, 486(3-5):75-174.
45. Ford L.R., Fulkerson D.R. Flows in Networks 2011, Princeton University Press.
46. Gaubert L., Redou P., Harrouet F., et al. Analyse mathématique du tri du couvain par les fourmis: auto-organisation fonctionnelle dénuée d'intelligence collective. JFSMA 2007 2007, 13-22. Cepadues Editions. V. Camps, P. Mathieu (Eds.).
47. Gibson M.J., Keedwell E.C., Savi D.A. An investigation of the efficient implementation of cellular automata on multi-core CPU and GPU hardware. Journal of Parallel and Distributed Computing 2015, 77:11-25.
48. Gilbert E.N. Random graphs. The Annals of Mathematical Statistics 1959, 30(4):1141-1144.
49. Girvan M., Newman M.E.J. Community structure in social and biological networks. Proceedings of the National Academy of Sciences 2002, 99(12):7821-7826.
50. Godara A., Lassarre S., Banos A. Simulating pedestrian-vehicle interaction in an urban network using cellular automata and multi-agent models. Traffic and Granular Flow '05 2007, 411-418. Springer. A. Schadschneider, T. Pöschel, R. Kühne (Eds.).
51. Goldberg D.E. Genetic Algorithms in Search, Optimization, and Machine Learning 1989, Addison-Wesley.
52. Goss S., Aron S., Deneubourg J.L., et al. Self-organized shortcuts in the Argentine ant. Naturwissenschaften 1989, 76(12):579-581.
53. Grassé P.-P. La reconstruction du nid et les coordinations interindividuelles chez Bellicositermes Natalensis et Cubitermes sp. la théorie de la stigmergie: Essai d'interprétation du comportement des termites constructeurs. Insectes Sociaux March 1959, 6(1):41-80.
54. Greenshields B., Channing W., Miller H., et al. A study of traffic capacity. Highway Research Board Proceedings 1935, National Research Council (USA).
55. Grimm V., Revilla E., Berger U., et al. Pattern-oriented modeling of agent-based complex systems: lessons from ecology. Science November 2005, 310(5750):987-991.
56. Hamdi A., Antoine V., Monmarché N., et al. Artificial ants for automatic classification. Artificial Ants. From Collective Intelligence to Real-life Optimization and Beyond 2010, 266-287. Wiley. N. Monmarché, F. Guinand, P. Siarry (Eds.).
57. Harvey W., Leake C.D. Exercitatio Anatomica de Motu Cordis et Sanguinis in Animalibus 1928, Thomas, Springfield III, available at. http://www.biodiversitylibrary.org/bibliography/6405.
58. Hassoumi I., Lang C., Marilleau N., et al. Toward a spatially-centered approach to integrate heterogeneous and multi-scales urban component models 2012, 81-86.
59. Heppner F., Grenander U. A stochastic nonlinear model for coordinated bird flocks. The Ubiquity of Chaos 1990, 233-238. AAAS. S. Krassner (Ed.).
60. Hewitt C., Bishop P., Steiger R. A universal modular ACTOR formalism for artificial intelligence 1973, 235-245.
61. Holland J.H. Adaptation in Natural and Artificial Systems 1992, MIT Press.
62. Kennedy J., Eberhart R.C. Swarm Intelligence 2001, Morgan Kaufmann Publishers.
63. Kermack W.O., Mckendrick A.G. A contribution to the mathematical theory of epidemics. Proceedings of the Royal Society of London A: Mathematical, Physical and Engineering Sciences 1927, 115(772):700-721.
64. Kirkpatrick S., Gelatt C.D., Vecchi M.P. Optimization by simulated annealing. Science 1983, 220(4598):671-680.
65. Kubera Y., Mathieu P., Picault S. IODA: an interaction-oriented approach for multi-agent based simulations. Autonomous Agents and Multi-Agent Systems 2011, 23(3):303-343.
66. König D. Theory of Finite and Infinite Graphs 1990, Birkhäuser, Boston.
67. Laporte G. The traveling salesman problem: An overview of exact and approximate algorithms. European Journal of Operational Research 1992, 59(2):231-247.
68. Lebacque J.-P. The Godunov scheme and what it means for first order traffic flow models. Internaional Symposium on Transportation and Traffic Theory 1996, 647-677.
69. Lemoigne J.-L. La mémoire du réseau: tout s'écouleet pourtant. Flux 1990, 6(2):25-32.
70. Lighthill M.J., Whitham G.B. On kinematic waves. II. A theory of traffic flow on long crowded roads. Proceedings of the Royal Society of London A: Mathematical, Physical and Engineering Sciences 1955, 229(1178):317-345.
71. Martin M., Chopard B., Albuquerque P. Formation of an ant cemetery: swarm intelligence or statistical accident?. Future Generation Computer Systems 2002, 18(7):951-959.
72. Mcconnell S. Code Complete, Second Edition 2004, Microsoft Press.
73. Michener C.D. Comparative social behavior of bees. Annual Review of Entomology 1969, 14(1):299-342.
74. Morin E. La méthode, Tome 1: la nature de la nature 1977, Seuil, Paris.
75. Musso P. Critique des réseaux 2003, Presses universitaires de France.
76. Nagel K., Schreckenberg M. A cellular automaton model for freeway traffic. Journal de Physique I 1992, 2(12):2221-2229.
77. Éducation Nationale épreuve de Mathématiques - Spécialité du baccalauréat ES 2009.
78. Newman M.E., Girvan M. Finding and evaluating community structure in networks. Physical Review E 2004, 69(2):026113.
79. Newman M.E. Modularity and community structure in networks. Proceedings of the National Academy of Sciences 2006, 103(23):8577-8582.
80. Quesnel G., Duboz R., Versmisse D., et al. DEVS coupling of spatial and ordinary differential equations: VLE framework. OICIMS 2005, 5:281-294.
81. Raghavan U.N., Albert R., Kumara S. Near linear time algorithm to detect community structures in large-scale networks. Physical Review E 2007, 76(3):036106.
82. Rego C., Gamboa D., Glover F., et al. Traveling salesman problem heuristics: Leading methods, implementations and latest advances. European Journal of Operational Research June 2011, 211(3):427-441.
83. Resnick M. Turtles, Termites, and Traffic Jams 1994, MIT Press.
84. Reuillon R., Leclaire M., Rey-Coyrehourcq S. OpenMOLE, a workflow engine specifically tailored for the distributed exploration of simulation models. Future Generation Computer Systems 2013, 29(8):1981-1990.
85. Reynolds C.W. Flocks, herds and schools: A distributed behavioral model. Computer Graphics 1987, 21(4):25-34.
86. Rey-Coyrehourcq S. Une plateforme intégrée pour la construction et l'évaluation de modèles de simulation en géographie available at. http://these.sebastienreycoyrehourcq.fr/.
87. Richards P.I. Shock waves on the highway. Operations Research 1956, 4(1):42-51.
88. Rousset A., Herrmann B., Lang C., et al. Using nested graphs to distribute parallel and distributed multi-agent systems 2016.
89. Saussure F.D., Bally C., De Mauro T. Cours de Linguistique Générale 1993, Payot.
90. Schreckenberg M., Schadschneider A., Nagel K., et al. Discrete stochastic models for traffic flow. Physical Review E 1995, 51(4):2939.
91. Schadschneider A. Traffic flow: a statistical physics point of view. Physica A: Statistical Mechanics and its Applications 2002, 313(1):153-187.
92. Schmitt C., Rey-Coyrehourcq S., Reuillon R., et al. Half a billion simulations: Evolutionary algorithms and distributed computing for calibrating the simpoplocal geographical model. Environment and Planning B: Planning and Design 2015, 42(2):300-315.
93. Scultetus A.H., Villavicencio J., Rich N.M. Facts and fiction surrounding the discovery of the venous valves. Journal of Vascular Surgery 2001, 33(2):435-441.
94. Theraulaz G., Bonabeau E., Nicolis S.C., et al. Spatial patterns in ant colonies. Proceedings of the National Academy of Sciences 2002, 99(15):9645-9649.
95. Thiele J.C., Grimm V. NetLogo meets R: Linking agent-based models with a toolbox for their analysis. Environmental Modelling and Software 2010, 25(8):972-974.
96. Treuil J.-P., Drogoul A., Zucker J.-D. Modélisation et Simulation à Base d'Agents 2008, Dunod.
97. Tromp J., Farneback G. Combinatorics of Go. Computers and Games 2007, 72-83. Springer. van den Herik, H. Ciancarini, P. Donkers (Eds.).
98. Tutte W.T. How to draw a graph. Proceedings of the London Mathematical Society 1963, 3-13(1):743-767.
99. Underwood R.T. Speed, volume, and density relationships 1961, Bureau of Highway Traffic, Yale University.
100. Valcke S., Balaji V., Craig A., et al. Coupling technologies for earth system modelling. Geoscientific Model Development 2012, 5(6):1589-1596.
101. Von Neumann J.V. Theory of Self-Reproducing Automata 1966, University of Illinois Press.
102. van Wageningen-Kessels F., van Lint H., Vuik K., et al. Genealogy of traffic flow models. EURO Journal on Transportation and Logistics 2015, 4(4):445-473.
103. Watts D.J., Strogatz S.H. Collective dynamics of 'small-world'networks. Nature 1998, 393(6684):440-442.
104. Multiagent Systems: A Modern Approach to Distributed Artificial Intelligence 1999, MIT Press. G. Weiss (Ed.).
105. Weise T. Global Optimization Algorithms - Theory and Application available at:. http://www.it-weise.de.
106. Wilensky U.J. NetLogo Ants model, Center for Connected Learning and Computer-based Modeling, Northwestern University available at. http://ccl.northwestern.%20edu/netlogo/models/Ants.
107. Wilson E.O. Sociobiology: the New Synthesis 2000, Belknap Press of Harvard University Press.
108. Wilson E.O., Holldobler B. Eusociality: Origin and consequences. Proceedings of the National Academy of Sciences 2005, 102(38):13367-13371.
109. Wilensky U. Mouse Drag One Example https://modelingcommons.org/%20browse/one_model/2330#model_tabs_browse_info.
110. Zeigler B.P., Moon Y., Kim D., et al. The DEVS environment for high-performance modeling and simulation. IEEE Computational Science & Engineering 1997, 4(3):61-71.