Abstract
The Reversed Compound Agent Theorem (RCAT) is a compositional result that uses Markovian process algebra to derive the reversed process of two cooperating continuous time Markov chains at equilibrium, under certain conditions. From this reversed process, together with the given, forward process, the joint state probabilities can be expressed as a product-form.We introduce MEERCAT, the first implementation of the RCAT, which classifies models where the theorem can be applied, and generates their product-form solutions.
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