FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W4310490601> ?p ?o ?g. }

• W4310490601 abstract "Agent-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.). The 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, Multilevel Agent-Based Modeling (ML-ABM), which is most often presented as an approach that extends the classical ABM paradigm to include multilevel concepts. Over 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. However, due to the youth of the field, no single definition, methodology, or tool unifies studies in this rapidly expanding area. This 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 SESs 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. However, 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. Different 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. In 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." @default.
• W4310490601 created "2022-12-11" @default.
• W4310490601 creator A5019608995 @default.
• W4310490601 creator A5048607259 @default.
• W4310490601 creator A5057389694 @default.
• W4310490601 date "2022-12-01" @default.
• W4310490601 modified "2023-09-30" @default.
• W4310490601 title "Handling multiple levels in agent-based models of complex socio-environmental systems: A comprehensive review" @default.
• W4310490601 cites W1494224259 @default.
• W4310490601 cites W1536565715 @default.
• W4310490601 cites W1571811746 @default.
• W4310490601 cites W1588942736 @default.
• W4310490601 cites W1895163321 @default.
• W4310490601 cites W1898986177 @default.
• W4310490601 cites W1979058254 @default.
• W4310490601 cites W1983672500 @default.
• W4310490601 cites W1988553173 @default.
• W4310490601 cites W2019721709 @default.
• W4310490601 cites W2020107552 @default.
• W4310490601 cites W2030938756 @default.
• W4310490601 cites W2045514650 @default.
• W4310490601 cites W2078832464 @default.
• W4310490601 cites W2085593420 @default.
• W4310490601 cites W2093971371 @default.
• W4310490601 cites W2125679751 @default.
• W4310490601 cites W2144246892 @default.
• W4310490601 cites W2152424089 @default.
• W4310490601 cites W2163722378 @default.
• W4310490601 cites W2169314507 @default.
• W4310490601 cites W2278920641 @default.
• W4310490601 cites W2317401576 @default.
• W4310490601 cites W2335535094 @default.
• W4310490601 cites W2467162868 @default.
• W4310490601 cites W2513172296 @default.
• W4310490601 cites W2549730987 @default.
• W4310490601 cites W2553838540 @default.
• W4310490601 cites W2561002798 @default.
• W4310490601 cites W2590118603 @default.
• W4310490601 cites W2599913900 @default.
• W4310490601 cites W2754698287 @default.
• W4310490601 cites W2783589141 @default.
• W4310490601 cites W2886266571 @default.
• W4310490601 cites W2889481070 @default.
• W4310490601 cites W2905771342 @default.
• W4310490601 cites W2909895012 @default.
• W4310490601 cites W2970509049 @default.
• W4310490601 cites W2980755542 @default.
• W4310490601 cites W3004055696 @default.
• W4310490601 cites W3024223917 @default.
• W4310490601 cites W3036852196 @default.
• W4310490601 cites W3106560182 @default.
• W4310490601 cites W3112303996 @default.
• W4310490601 cites W3159222905 @default.
• W4310490601 cites W3192711559 @default.
• W4310490601 cites W3197063322 @default.
• W4310490601 cites W4229376488 @default.
• W4310490601 cites W4238471284 @default.
• W4310490601 cites W4243813913 @default.
• W4310490601 cites W4288855047 @default.
• W4310490601 cites W4298216327 @default.
• W4310490601 cites W71430541 @default.
• W4310490601 doi "https://doi.org/10.3389/fams.2022.1020353" @default.
• W4310490601 hasPublicationYear "2022" @default.
• W4310490601 type Work @default.
• W4310490601 citedByCount "1" @default.
• W4310490601 countsByYear W43104906012023 @default.
• W4310490601 crossrefType "journal-article" @default.
• W4310490601 hasAuthorship W4310490601A5019608995 @default.
• W4310490601 hasAuthorship W4310490601A5048607259 @default.
• W4310490601 hasAuthorship W4310490601A5057389694 @default.
• W4310490601 hasBestOaLocation W43104906011 @default.
• W4310490601 hasConcept C112930515 @default.
• W4310490601 hasConcept C127413603 @default.
• W4310490601 hasConcept C154945302 @default.
• W4310490601 hasConcept C169087156 @default.
• W4310490601 hasConcept C17744445 @default.
• W4310490601 hasConcept C199539241 @default.
• W4310490601 hasConcept C202444582 @default.
• W4310490601 hasConcept C2522767166 @default.
• W4310490601 hasConcept C2776359362 @default.
• W4310490601 hasConcept C33923547 @default.
• W4310490601 hasConcept C39890363 @default.
• W4310490601 hasConcept C41008148 @default.
• W4310490601 hasConcept C539667460 @default.
• W4310490601 hasConcept C66938386 @default.
• W4310490601 hasConcept C71924100 @default.
• W4310490601 hasConcept C94625758 @default.
• W4310490601 hasConcept C9652623 @default.
• W4310490601 hasConceptScore W4310490601C112930515 @default.
• W4310490601 hasConceptScore W4310490601C127413603 @default.
• W4310490601 hasConceptScore W4310490601C154945302 @default.
• W4310490601 hasConceptScore W4310490601C169087156 @default.
• W4310490601 hasConceptScore W4310490601C17744445 @default.
• W4310490601 hasConceptScore W4310490601C199539241 @default.
• W4310490601 hasConceptScore W4310490601C202444582 @default.
• W4310490601 hasConceptScore W4310490601C2522767166 @default.
• W4310490601 hasConceptScore W4310490601C2776359362 @default.
• W4310490601 hasConceptScore W4310490601C33923547 @default.
• W4310490601 hasConceptScore W4310490601C39890363 @default.
• W4310490601 hasConceptScore W4310490601C41008148 @default.

• next