Agent-based modeling (ABM) has been widely employed by researchers in various
domains. Developing valid and useful agent-based models (ABMs) imposes challenges on …

Agent-based models (ABMs) are particularly suited for simulating the behaviour of
agricultural agents in response to land use (LU) policy. However, there is no evidence of …

Technological change co‐determines agri‐environmental performance and farm structural
transformation. Meaningful impact assessment of related policies can be derived from farm …

Agent-based modeling (ABM) has become popular since it allows a direct representation of
heterogeneous individual entities, their decisions, and their interactions, in a given space …

Agent‐based models have diversified their applications across various domains due to the
ease with which different phenomena can be represented and simulated. These models …

Agent-based modelling is a powerful tool when simulating human systems, yet when human
behaviour cannot be described by simple rules or maximizing one's own profit, we quickly …

This study investigates how the investor structures affect the corn futures price volatility using
corn futures and spot price daily data ranging from 5 January 2009 to 31 December 2022 …

Novel developments in artificial intelligence excel in regard to the abilities of rule-based
agent-based models (ABMs), but are still limited in their representation of bounded …

This chapter discusses the challenges, complexities, and benefits of using agent-based
modelling in the study and practice of leadership in teams and organizations. After …

Agent-Based Models are very useful for simulation of physical or social processes, such as
the spreading of a pandemic in a city. Such models proceed by specifying the behavior of …