Abstract
Treating random phenomena in concurrency theory has a long tradition. Petri nets [18,10] and process algebras [14] have been extended with probabilities. The same applies to behavioural semantics such as strong and weak (bi)simulation [1], and testing pre-orders [5]. Beautiful connections between probabilistic bisimulation [16] and Markov chain lumping [15] have been found. A plethora of probabilistic concurrency models has emerged [19]. Over the years, the focus shifted from covering discrete to treating continuous stochastic phenomena [12,13].
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Katoen, JP. (2013). Concurrency Meets Probability: Theory and Practice. In: D’Argenio, P.R., Melgratti, H. (eds) CONCUR 2013 – Concurrency Theory. CONCUR 2013. Lecture Notes in Computer Science, vol 8052. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-40184-8_4
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DOI: https://doi.org/10.1007/978-3-642-40184-8_4
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