AINeutralarXiv – CS AI · 7h ago6/10
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Extending Causal Metamodeling to a non-Markovian Queue
Researchers extended modular dynamic Bayesian networks (MDBNs) to model non-Markovian queuing systems by approximating non-exponential distributions with phase-type distributions. This advancement enables causal metamodeling for complex systems previously limited to Markovian analysis, achieving orders-of-magnitude speedup in inference compared to direct simulation.