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The Reversed Compound Agent Theorem (RCAT) is a compositional result that uses Markovian process algebra (MPA) to derive the reversed process of certain interactions between two continuous time Markov chains at equilibrium. From this reversed process, together with the given, forward process, the joint state probabilities can be expressed as a product-form,(More)
We present a process algebra or programming language, based on CCS, which may be used to describe discrete event simulations with parallelism. It has extensions to describe the passing of time and probabilistic choice, either discrete, between a countable number of processes, or continuous to choose a random amount of time to wait. It has a clear(More)
EEcient product form solution is one of the major attractions of queueing networks for performance modelling purposes. These models rely on a form of interaction between nodes in a network which allows them to be solved in isolation, since they behave as if independent up to normalisation. Markovian process algebras (MPA) extend classical process algebras(More)
Stochastic networks defined by a collection of cooperating agents are solved for their equilibrium state probability distribution by a new compositional method. The agents are processes formalised in a Markovian Process Algebra , which enables the reversed stationary Markov process of a cooperation to be determined symbolically under appropriate conditions.(More)