Because of the many interacting elements at the airport, the uncertainty in system behavior, and the degree of human agency involved, the airport has become a highly complex system. Its overall behavior is influenced by dynamic interactions between distributed elements in a rapidly changing and unpredicted environment. Motivated by the need to understand such a complex system, this research explores an agent-based approach to model the airport airside behavior emerging from the interactions between various system elements both at the airport and TMA. Agent-Based Modeling is increasingly recognized as a powerful approach to simulate complex systems, because it can represent important phenomena resulting from the characteristics and behaviors of individual agents. These phenomena are usually referred to as emergence which is a key property of complex systems. Unlike existing models which tend to capture the impact on one Key Performance Area (KPA) without considering other KPAs, the objective of this research is to model and optimize the airport airside behavior in terms of multiple KPAs being safety, capacity, economy, and sustainability. This paper presents the results of the first step of this research which is about identifying the human agents relevant for airport modeling and mapping their goals in terms of the various KPAs.