6533b834fe1ef96bd129df2b

RESEARCH PRODUCT

A generic model of reinforcement learning combined with macroscopic cellular automata to simulate land use change

Mohamed NemicheRafael Pla LópezFatima Ezahra Sfa

subject

ComputingMilieux_GENERALLand useComputer sciencebusiness.industryEnvironmental resource managementLand managementComplex systemReinforcement learningLand use land-use change and forestryLand coverbusinessField (geography)Cellular automaton

description

Better understanding the evolution of land cover is a priority concern in the field of land use change study. This evolution can be the result of interactions between major factors. The study of land use change is included in territorial planning to inform planners and policy makers of possible developments they will face. Land use models are useful for reasonable land use management to optimize future land management decisions. In this paper we present an original theoretical model of reinforcement learning combined with macroscopic cellular automata to simulate land use change.

yearjournalcountryeditionlanguage
2019-04-012019 4th World Conference on Complex Systems (WCCS)
https://doi.org/10.1109/icocs.2019.8930751