Decision-support systems can be used to measure the complexity of systems as well as forecast and analyse policies. Agent-based modelling (ABM) is a relatively new approach for modelling complex systems in which independent and interconnected agents play a role. Simulations aid in estimating and comprehending evolving patterns that necessitate the development of new legislation for local agents to change the structure incrementally. This study uses this approach to create the Befergyonet ABM, which is used to run computer simulations in a spatio-intertemporal environment on beef cattle. The methodology presented in this paper is solely intended to encourage the use of cutting-edge computer programmes to simulate complex structures as a means of representing real-world events, and it can serve as a methodological guide for readers interested in creating their own ABM. This research can also serve as a useful example of how ABM can contribute to solutions that are more efficient and consistent with both private and societal outcomes, given the increasing interest in optimal natural resource allocation under alternative carbon sequestration, price, and policy regimes, as well as climate-based uncertainty.
Author (s) Details
Inocencio Rodríguez González
Department of Social Sciences, University of Puerto Rico-Arecibo, Puerto Rico
Gerard E. D’Souza
College of Agriculture and Human Sciences, Prairie View A&M University, Texas, USA
View Book :- https://stm.bookpi.org/CIEES-V3/article/view/721