Stochastic Petri Net Representation of Discrete Event Simulations
IEEE Transactions on Software Engineering
Likelihood ratio gradient estimation for stochastic systems
Communications of the ACM - Special issue on simulation
Structural conditions for perturbation analysis of queueing systems
Journal of the ACM (JACM)
GMSim: a tool for compositional GSMP modeling
Proceedings of the 30th conference on Winter simulation
Problems in Bayesian analysis of stochastic simulation
WSC '86 Proceedings of the 18th conference on Winter simulation
Analytic representations of simulation
WSC '84 Proceedings of the 16th conference on Winter simulation
Ontologies for modeling and simulation: issues and approaches
WSC '04 Proceedings of the 36th conference on Winter simulation
PMaude: Rewrite-based Specification Language for Probabilistic Object Systems
Electronic Notes in Theoretical Computer Science (ENTCS)
All about maude - a high-performance logical framework: how to specify, program and verify systems in rewriting logic
Simulation-based performance analysis of channel-based coordination models
COORDINATION'11 Proceedings of the 13th international conference on Coordination models and languages
Bio-PEPAd: A non-Markovian extension of Bio-PEPA
Theoretical Computer Science
HASL: an expressive language for statistical verification of stochastic models
Proceedings of the 5th International ICST Conference on Performance Evaluation Methodologies and Tools
Modeling paradigms for discrete event simulation
Operations Research Letters
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A generalized semi-Markov process (GSMP) is a stochastic process description of a large class of discrete-event simulations. GSMP's are defined, and some basic properties of GSMP's are described. It is argued that GSMP's provide a convenient frame-work in which to analyze many questions of interest to practitioners.