A review and classification of combined simulation
Computers and Industrial Engineering
Programming combined discrete-continuous simulation models for performance
WSC '96 Proceedings of the 28th conference on Winter simulation
Parallel and Distribution Simulation Systems
Parallel and Distribution Simulation Systems
Neural Networks and Simulation Methods
Neural Networks and Simulation Methods
Simulation Modeling and Analysis
Simulation Modeling and Analysis
Mixed-Mode Simulation and Analog Multilevel Simulation
Mixed-Mode Simulation and Analog Multilevel Simulation
Theory of Modeling and Simulation
Theory of Modeling and Simulation
Proceedings of the First International Workshop on Multi-Agent Systems and Agent-Based Simulation
Proceedings of the First International Workshop on Multi-Agent Systems and Agent-Based Simulation
Proceedings of the 35th conference on Winter simulation: driving innovation
Applying statistical control techniques to air traffic simulations
WSC '04 Proceedings of the 36th conference on Winter simulation
A hybrid modelling framework to simulate disaster response decisions
International Journal of Advanced Intelligence Paradigms
Aviation safety: modeling and analyzing complex interactions between humans and automated systems
Proceedings of the 3rd International Conference on Application and Theory of Automation in Command and Control Systems
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Hybrid agent-based simulation is required to provide a mechanism for analyzing large-scale complex systems, such as the National Airspace System (NAS). The dynamic behavior of many complex systems is, in general, hybrid in nature and can be best described by a combination of discrete-event and continuous-time models, and their interactions. Correspondingly, hybrid agent-based simulation capable of incorporating different types of models provides an accurate means of evaluating the reliability and performance of complex systems. However, in order to serve as a design and analysis tool, a number of issues must be addressed. This paper outlines issues in the development of hybrid agent-based simulation architectures capable of providing a scaleable mechanism for simulating the NAS. In particular, an object-oriented approach is described. In addition, methods of improving computational efficiency of updating the simulation are described and compared.