Qualitative physics: past, present, and future
Exploring artificial intelligence
Simulation modeling with event graphs
Communications of the ACM
The implementation of temporal intervals in qualitative simulation graphs
ACM Transactions on Modeling and Computer Simulation (TOMACS)
Execution Conditions: A Formalization of Event Cancellation in Simulation Graphs
INFORMS Journal on Computing
Estimating the probability of an event execution in qualitative discrete event simulation
Proceedings of the Winter Simulation Conference
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Event Graphs (EGs) and Simulation Graph Models provide a powerful and general modeling framework for discrete event simulation. Qualitative Event Graphs (QEGs) extend the EG framework to a qualitative approach to discrete-event simulation. In QEG, the uncertainty in event execution times is represented by a closed interval in the set of real numbers. When two or more event execution intervals overlap, multiple event execution sequences or threads result. This leads to simulation output in the form of multiple threads. In general, the number of threads can explode exponentially making output difficult to analyze. In this paper, we introduce three scoring methods to rank the threads on the relative likelihood of their event execution sequences. We discuss the assumptions of these methods along with their advantages and disadvantages. Depending on the needs of the user, scoring and ranking could help eliminate the need to execute some threads and cut the execution time of the simulation.