Applications
Agent-based models have been used since the mid-1990s to solve a variety of business and technology problems. Examples of applications include the modeling of organizational behaviour and cognition, team working, supply chain optimization and logistics, modeling of consumer behavior, including word of mouth, social network effects, distributed computing, workforce management, and portfolio management. They have also been used to analyze traffic congestion. In these and other applications, the system of interest is simulated by capturing the behavior of individual agents and their interconnections. Agent-based modeling tools can be used to test how changes in individual behaviors will affect the system's emerging overall behavior.
Other models have analyzed the spread of epidemics, the threat of biowarfare, biological applications including population dynamics, the growth and decline of ancient civilizations, evolution of ethnocentric behavior, forced displacement/migration, language choice dynamics, cognitive modeling, and biomedical applications including inflammation and the human immune system. Agent-based models have also been used for developing decision support systems such as for breast cancer. Military applications have been evaluated in.
Since the beginning of the 20th century ABMs have been deployed in architecture and urban planning to evaluate design and to simulate pedestrian flow in the urban environment.
Recently, agent based modelling and simulation has been applied to various domains such as studying the impact of publication venues by researchers in the computer science domain (journals versus conferences). In addition, ABMS has been used to simulate information delivery in ambient assisted environments. In the domain of peer-to-Peer, ad-hoc and other self-organizing and complex networks, the usefulness of agent based modeling and simulation has been shown. The use of Computer Science based Formal Specification framework coupled with Wireless sensor networks and an Agent-based simulation has recently been demonstrated.
Agent based evolutionary search or algorithm is a new research topic for solving complex optimization problems.
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