@incollection{fdi:010094649, title = {{G}rowing bioinspired synthetic landscape ecologies and the adequacy of object oriented programming}, author = {{L}e {F}ur, {J}ean and {M}boup, {P}.{A}. and {S}all, {M}.}, editor = {}, language = {{ENG}}, abstract = {{I}n 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. {F}aced 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. {T}hese were then generalized and consolidated to form a coherent platform. {T}o address robustness, the model was continually reworked in search of the closest resemblance to the concrete workings of {N}ature. {W}e have arrived at a general architecture built from the bottom up that is both generic and as parsimonious as possible. {T}he 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. {T}he 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.}, keywords = {{SENEGAL}}, booktitle = {{S}imulation and modeling methodologies, technologies and applications : {I}nternational {O}nline {C}onference ({SIMULTECH} 2021)}, numero = {601}, pages = {118--137}, address = {{C}ham}, series = {{L}ecture {N}otes in {N}etworks and {S}ystems}, year = {2023}, DOI = {10.1007/978-3-031-23149-0_7}, ISBN = {978-3-031-23148-3}, URL = {https://www.documentation.ird.fr/hor/fdi:010094649}, }