A Survey of Emergent Behavior and Its Impacts in Agent-based Systems

Abstract

Increasingly, software agents are evolving from the roles of facilitators into decision-makers in managing complex, real-time systems such as logistics enterprise. Emergent behavior is that which is not attributed to any individual (agent), but is a global outcome of individual (agent) coordination. While agent's degree of autonomy and responsibility will continue to increase with time, the impact of emergent behavior in agent system on the performance and stability of these systems become an important issue. We found that emergent behavior is a major concern of potential users while we try to apply agent technology to such industry areas as transportation planning and logistics coordination. To really make agent technology work in industry convincingly, it is valuable to do a study of emergent behaviour and its impacts to the application of agent technology. This paper reviews the research on emergent behaviour, discuss its research challenge and application impact, and suggest research directions on agent emergent behaviour.

Influence of countries adopted social distancing policy for COVID-19 reduction under the view of the airborne transmission framework

“…Many diseases share in common the same forms of infection as COVID-19 [2], however, not only the causes of transmission are important issues to be considered, as the chemical and biological properties of transmission forms and the virus-human biological affinity (coronavirus-membrane-fusion activation), but the human emergent behavior events [18,19,20,21] since it is in the main cause of virus community transmission patterns. All those three mentioned parameters share a high convergent solutions (affinity) if observed with a nonlinear time series analysis [9, 22,23], thus presenting possibly high asymptotic stability for the dissemination network [24].…”

“…To conclude the previous paragraph statements, the analyzed mathematical framework of this review, points that the transmission and infection patterns resemble the own host emergent behavior [18,19,20,21], and for this reason it assumes the infodemics domains of analysis in a multidimensional forms, the heteroskedasticity aspect, in which SIR models can not handle this feature by its three main variables components. Therefore, the virus reproduction need to be quantified, as it is designed theoretically in this review, with a high order organization of the host individual/group/community behavior [17] in the outside scope of the strictly SIR models basis.…”

Identifying and Quantifying Emergent Behavior Through System of Systems Modeling and Simulation

“…Macal and North (2008) states that when the behavior of an agent affects other agents, and those agents' behaviors ultimately affect the original agent, a complex feedback dynamic is put in motion that produces emergence. Li, Sim, and Low (2006) states that software agents cannot act like people due to speed of their decisions, lack of flexibility, and learning difficulties. Therefore, they can act in unexpected ways.…”

A Mechanism for Recognizing and Suppressing the Emergent Behavior of UAV Swarm

“…Most of the scholars [1][2][3] once stated that the emergent behavior is produced by a number of local interactions among individuals. Forrest [4] also made the following definition: "a group of individuals create incidental phenomenon at macro level during interaction process, and the incidental phenomenon is explained by computation results".…”