@article{fdi:010086763,
  title = {{H}andling multiple levels in agent-based models of complex socio-environmental systems : a comprehensive review},
  author = {{B}rugi{\`e}re, {A}. and {D}oanh, {N}. {N}. and {D}rogoul, {A}lexis},
  editor = {},
  language = {{ENG}},
  abstract = {{A}gent-based modeling ({ABM}) has been successfully used, since its emergence in the 1990s, to model and simulate the dynamics at work in complex socio-environmental systems, in many domains and applications where interactions between people and their environments give rise to emergent phenomena that are difficult to study otherwise (urban planning, land-use change, adaptation to environmental changes, biodiversity protection in socio-ecosystems, environmental pollution control, etc.). {T}he inclusion of multiple levels of analysis, abstraction, and representation in these models, however, is much more recent and is still the subject of many proposals and discussions within a relatively informal field, {M}ultilevel {A}gent-{B}ased {M}odeling ({ML}-{ABM}), which is most often presented as an approach that extends the classical {ABM} paradigm to include multilevel concepts. {O}ver the past decade, {ML}-{ABM} has been increasingly adopted and explored by researchers as an effective paradigm for framing and defining the mechanisms underlying multilevel dynamics. {H}owever, due to the youth of the field, no single definition, methodology, or tool unifies studies in this rapidly expanding area. {T}his review will begin with an introduction to socio-environmental systems ({SES}) and the challenges that modeling approaches face in representing them properly, especially regarding the complexity of human behaviors and organizations. {ABM} presents opportunities for modeling {SES}s with respect to these challenges, including the simulation of individual and social behavior and their ability to provide a descriptive and generative representation of the simulated system. {H}owever, {ABM} is limited in its ability to represent levels and scales, as these concepts are absent from the classical {ABM} metamodel. {A} complete review of the {ML}-{ABM} literature will be carried out, structured around a continuum that emerged during the review: that of the distribution of behaviors (and thus, from a software engineering perspective, of control) across the levels, from approaches that allow only one level to be active at a time, to approaches that rely on simultaneous activity and feedback loops between several levels. {D}ifferent design choices will, thus, be presented to meet the different needs of multi-level representation, focusing on the interest on modelers and the strengths and limitations of each. {I}n particular, we will highlight a limitation shared by all the reviewed approaches, namely their inability to represent several parallel hierarchies of levels and their interactions, a capability that appears more and more crucial to finely represent social behaviors in {SES}. {A} new perspective on the interest that the {AGR} approach could represent to allow this representation of hierarchies allows us to conclude on the research perspectives are still open.},
  keywords = {review ; multi-level agent based model ; design pattern ; socio-environmental systems ({SES}) ; multi-level ; agent-based modeling},
  booktitle = {},
  journal = {{F}rontiers in {A}pplied {M}athematics and {S}tatistics},
  volume = {8},
  numero = {},
  pages = {1020353 [21 p.]},
  year = {2022},
  DOI = {10.3389/fams.2022.1020353},
  URL = {https://www.documentation.ird.fr/hor/fdi:010086763},
}