Abstract
In this study we develop, using basic object-oriented paradigms, and in collaboration with biologists, a comprehensive model of landscapes and ecosystems dynamics based on bioinspiration principles. Faced with the issue of taking into consideration a variety of elements, processes, interactions, contexts, and scales simultaneously effective, we iteratively develop this model using successive aggregation of new components based on specific case studies. These were then generalized and consolidated to form a coherent platform. To address robustness, the model was continually reworked in search of the closest resemblance to the concrete workings of Nature.
We have arrived at a general architecture built from the bottom up that is both generic and as parsimonious as possible. The model emerging from this compilation is a shared class tree with three primary categories of variability: (i) cognitive living agents, (ii) containers of agents that can be nested at various functional scales, and (iii) particular genomes that instantiate attributes for each type of agent. The results of the iterative strategy to modeling synthetic ecology are discussed, as well as the suitability of object-oriented paradigms (composition, aggregation, inheritance, generalization…) for achieving the goal of bioinspired modeling.
Parts of this work have been presented on behalf of the Simultech (Internat. Conf. Simul. and Model. Method., Technol. and Applic.) conferences (see [1, 2])
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Le Fur, J., Mboup, P.A., Sall, M.: A simulation model for integrating multidisciplinary knowledge in natural sciences. heuristic and application to wild rodent studies. In: 7th International Conference on Simulation and Modeling Methodologies, Technologies and Applications, pp. 340–347. Scitepress (2017)
Le Fur, J.; Mboup, P.A., Sall, M.: Use and adequacy of computer paradigms to simulate bioinspired synthetic landscape ecologies. In: 11th International Conference on Simulation and Modeling Methodologies, Technologies and Applications, pp. 154–162. Scitepress (2021)
Chen, Y.C., Lu, P.E., Chang, C.S., Liu, T.H.: A time-dependent SIR model for COVID-19 with undetectable infected persons. IEEE Trans. Netw. Sci. Eng. 7(4), 3279–3294 (2020)
Kari, L., Rozenberg, G.: The many facets of natural computing. Commun. ACM 51(10), 72–83 (2008)
Yao, X., Liu, Y., Li, J., He, J., Frayn, C.: Current developments and future directions of bio-inspired computation and implications for ecoinformatics. Eco. Inform. 1(1), 9–22 (2006)
Olden, J.D., Poff, N.L., Bledsoe, B.P.: Incorporating ecological knowledge into ecoinformatics: an example of modeling hierarchically structured aquatic communities with neural networks. Eco. Inform. 1(1), 33–42 (2006)
Colomer, M.À., Margalida, A., Sanuy, D., Pérez-Jiménez, M.J.: A bio-inspired computing model as a new tool for modeling ecosystems: the avian scavengers as a case study. Ecol. Model. 222(1), 33–47 (2011)
Holling, C.S.: The strategy of building models of complex ecological systems. In: Watt, K.E.F. (ed.) Systems Analysis in Ecology, pp. 195–214. Academic Press, Cambridge (1966)
Evans, M.R., et al.: Do simple models lead to generality in ecology? Trends Ecol. Evol. 28(10), 578–583 (2013)
Svoray, T., Benenson, I.: Scale and adequacy of environmental microsimulation. Ecol. Complex. 6(2), 77–79 (2009)
Dunham, M.J.: Synthetic ecology: a model system for cooperation. Proc. Natl. Acad. Sci. 104(6), 1741–1742 (2007)
Shou, W., Ram, S., Vilar, J.M.: Synthetic cooperation in engineered yeast populations. Proc. Natl. Acad. Sci. 104(6), 1877–1882 (2007)
Buck-Sorlin, G.: Functional-structural plant modeling. In: Dubitzky, W., Wolkenhauer, O., Cho, K.H., Yokota, H. (eds.) Encyclopedia of Systems Biology. Springer, New York, NY (2013)
Dejong, T., Da Silva, D., Vos, J., Escobar-Gutiérrez, A.: Using functional-structural plant models to study, understand and integrate plant development and ecophysiology. Ann. Bot. 108, 987–989 (2011)
Cantrell, B., Holzman, J.: Protocols, simulation, and manipulation for indeterminate landscapes. Synthetic Ecologies (2014)
DeAngelis, D.L., Mooij, W.M.: In praise of mechanistically rich models. In: Canham, C.D., Cole, J.J., Lauenroth, W.K. (eds.) Models in Ecosystem Science, pp. 63–82. Princeton University Press, New Jersey (2003)
Clapham, W.M., Crosby, C.J.: Utility of object-oriented programming in complex system modeling. Math. Comput. Modell. 16(617), 45–50 (1992)
Granjon, L., Duplantier, J.M.: Les rongeurs de l’Afrique sahélo-soudanienne. IRD Editions, Publications Scientifiques du Muséum - Collection Faune et Flore tropicales 43. (2009). ISBN IRD, 978-2-7099-1675-2
Le Fur, J.: A formal computer framework for linking multidisciplinary multiscale knowledge. a case study on rodent population dynamics and management. In: European Conference on Complex Systems (ECCS), Lisbon (2013a)
Le Fur, J.: Du foisonnement des disciplines à la recomposition d’une réalité partagée Élaboration d’une structure de modélisation dédiée à l’intégration de connaissances disciplinaires. In: XXIeme journées de Rochebrune “Multi-trans-interdisciplinarité”. Rencontres interdisciplinaires sur les systèmes complexes naturels et artificiels (2014). https://hal.ird.fr/ird-03182988
North, M.J., et al.: Complex adaptive systems modeling with repast simphony. Complex Adaptive Systems Modeling, Springer, Heidelberg (2013). https://doi.org/10.1186/2194-3206-1-3
Comte, A.: Caractérisation des barrières à l’hybridation de deux espèces jumelles de rongeurs africains du genre Mastomys. Étude par simulation multi-agents à partir de deux expériences in situ. Rapp. M2 Écologie-Biodiversité Spécialité Biodiversité Évolution Parcours Génétique et Biodiversité, p. 44 (2012)
Diakhate, E.H.M., Diouf, N., Granjon, L., Konate, K., Mboup, P.A., Le Fur J.: Modélisation et simulation multi-agents d’un protocole de capture-marquage-recapture d’une population de rongeurs sauvages dans la réserve de Bandia (Sénégal). In: 12th African Conference on Research in Computer Science and Applied Mathematics (CARI), Saint-Louis Sénégal, pp.43–54 (2014)
Mboup, P.A., Konaté, K., Handschumacher, P., Le Fur, J.: Des Connaissances au Modèle Multi-agents par l’approche orientée événement : construction d’un simulateur de la colonisation du rat noir au Sénégal par les transports humains sur un siècle. Actes Colloque National sur la Recherche en Informatique et ses Applications, Thiès, Sénégal, p. 8 (2015a)
Mboup, P.A., Mboup, M.L., Konaté, K., Handschumacher, P., Le Fur, J.: Optimisation de l’utilisation de l’algorithme de Dijkstra pour un simulateur multi-agents spatialisé. In: World Congress on Information Technology and Computer Applications (WCITCA), Hammamet, Tunisia, pp. 1–6 (2015b). https://doi.org/10.1109/WCITCA.2015.7367061
Sall, M., Dembélé, J.M., Le Fur, J.: An hybrid algorithm to simulate mice following residential wall. In: Proceedings of the 8th International Conference on Simulation and Modeling Methodologies, Technologies and Application (Simultech). ScitePress Publication, pp. 368–375 (2019)
Simon, H A.: The architecture of complexity. Proc. Am. Philos. Soc. 106(6), 467-482 (1962)
Le Fur, J.: Extending life concepts to complex systems Interdiscip. Descr. Complex Syst. 11(1), 37-50 (2013b)
Macia-Perez, F., Lorenzo-Fonseca, I., VicenteBerna-Martinez, J.: A formal framework for modelling complex network management systems. J. Netw. Comput. Appl. 40, 255–269 (2014)
Caillou, P., Gaudou, B., Grignard, A., Truong, C.Q., Taillandier, P.: A Simple-to-use BDI architecture for agent-based modeling and simulation. In: The 11th Conference of the European Social Simulation Association, Groningen, Netherlands hal-01216165 (2015)
Shaw, K.L., Wagner, K.: Cricketsim: a Genetic and Evolutionary Computer Simulation. J. Artificial Societies and Social Simulation, 11(3) (2008)
Forterre, P., Gribaldo, S., Brochier, C.: LUCA: à la recherche du plus proche ancêtre commun universel. Méd./Sci. 21(10), 860–865 (2005)
Darwin, C.: On the Origin of Species by Means of Natural Selection, or the Preservation of Favoured Races in the Struggle for Life. John Murray, London (1859)
Marcos, E., Cavero, J.M.: Hierarchies in object oriented conceptual modeling. In: Bruel, J.-M., Bellahsene, Z. (eds.) OOIS 2002. LNCS, vol. 2426, pp. 24–33. Springer, Heidelberg (2002). https://doi.org/10.1007/3-540-46105-1_4
Gell-Man, M.: The Quark and the Jaguar: Adventures in the Simple and the Complex. H. W. Freeman, New York (1994)
Le Fur, J., Sall, M.: Using flexible time scale to explore the validity of agent-based models of ecosystem dynamics: application to simulation of a wild rodent population in a changing agricultural landscape. In: 8th International Conference on Simulation and Modeling Methodologies, Technologies and Application, pp. 297–304. Scitepress (2018)
Ferber, J., Gutknecht, O., Michel, F.: From agents to organizations: an organizational view of multi agent systems. In: Giorgini, P., Müller, J.P., Odell, J. (eds.) Agent-Oriented Software Engineering IV, LNCS, vol. 2935, pp. 214–230. Springer, Berlin, Heidelberg (2003)
Mboup, P.A., Konaté, K., Le Fur, J.: A multi-world agent-based model working at several spatial and temporal scales for simulating complex geographic systems. In: International Conference on Computational Science (ICCS), Zurich, Procedia Computer Science 108C, 968–977 (2017)
Mohnen, M.: Interfaces with default implementations in Java. In: Proceedings of the Workshop on Intermediate Representation Engineering for Virtual Machines, pp. 35–40 (2002)
Malayeri, D., Aldrich, J.: CZ: multiple inheritance without diamonds. ACM SIGPLAN Notices 44(10), 21–40 (2009)
Truyen, E., Joosen, W., Nørregaard Jørgensen, B., Verbaeten, P.: A generalization and solution to the common ancestor dilemma problem in delegation-based object systems. In: Proceedings of the 2004 Dynamic Aspects Workshop, 103–119 (2004)
Acknowledgements
The authors would like to thank J.F. Cosson, J.P. Quéré, C. Berthier, B. Gauffre, J.M. Duplantier, L. Granjon, G. Ganem, J. Britton, O. Ninot, J. Lombard, P. Handschumacher, S. Piry, the scientists who kindly agreed to decipher their disciplinary expertise for the formalization of thematic case studies. This study owes much to the work done by Q. Baduel, A. Realini, J.E. Longueville, A. Comte and M. Diakhate, as part of their student internships. The study was supported by the Chancira (grant IRD-ANR-11-CEPL-0010), Cerise (grant IRD-FRB no. AAP-SCEN -20B III) projects, the French National Research Institute for Sustainable Development (IRD) and the ‘Centre de Biologie pour la Gestion des Populations’ (CBGP, UMR no. 22 INRAe/IRD/Cirad/Supagro). We also wish to thank the members of the BioPASS laboratory in Senegal for their decisive field support.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2023 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this paper
Cite this paper
Le Fur, J., Mboup, P.A., Sall, M. (2023). Growing Bioinspired Synthetic Landscape Ecologies and the Adequacy of Object Oriented Programming. In: Wagner, G., Werner, F., Oren, T., De Rango, F. (eds) Simulation and Modeling Methodologies, Technologies and Applications. SIMULTECH 2021. Lecture Notes in Networks and Systems, vol 601. Springer, Cham. https://doi.org/10.1007/978-3-031-23149-0_7
Download citation
DOI: https://doi.org/10.1007/978-3-031-23149-0_7
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-031-23148-3
Online ISBN: 978-3-031-23149-0
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)