Salīdzināt metodes

	Aģentu bāzēta rindošanās simulācija	Aģentu modelēšana (ABM)
Nozare	Simulācija	Simulācija
Saime	Process / pipeline	Process / pipeline
Izcelsmes gads	2000s	1970s–1990s (formalized as a field)
Autors	Macal, C. M. & North, M. J. (hybrid formalization); queueing theory rooted in Erlang (1909)	Thomas Schelling and Robert Axelrod (foundational contributions, 1970s–1990s)
Tips	Hybrid simulation — agent-based + queueing	Computational simulation method
Pirmavots	Macal, C. M., & North, M. J. (2010). Tutorial on agent-based modelling and simulation. Journal of Simulation, 4(3), 151–162.	Axelrod, R. (1997). The Complexity of Cooperation: Agent-Based Models of Competition and Collaboration. Princeton University Press.
Citi nosaukumi	AB-QS, Agent-Based Queue Simulation, ABM Queueing, Agent Queue Simulation	ABM, Ajan Tabanlı Modelleme (ABM), multi-agent simulation, individual-based modeling
Saistītās	5	5
Kopsavilkums	Agent-Based Queueing Simulation (AB-QS) combines agent-based modeling with queueing theory to simulate systems where autonomous, decision-making entities interact through waiting lines and service points. Each entity (patient, customer, job) is modeled as an independent agent with its own state and behavioral rules, enabling richer, more realistic dynamics than classical queueing models alone.	Agent-based modeling (ABM) is a computational simulation method, formalized through the work of Thomas Schelling and Robert Axelrod in the 1970s–1990s, that simulates the behavior of complex systems by specifying and running autonomous agents — individuals, firms, cells, or any bounded entity — whose local interactions with each other and with their environment collectively produce global, system-level patterns that could not be predicted from any single agent's rules alone.