1. J. Adámek & H.-E. Porst (2004): On tree coalgebras and coalgebra presentations. Theoretical Computer Science 311, pp. 257–283, doi:10.1016/S0304-3975(03)00378-5.
  2. S. Andova, S. Georgievska & N. Trčka (2012): Branching bisimulation congruence for probabilistic systems. Theoretical Computer Science 413, pp. 58–72, doi:10.1016/j.tcs.2011.07.020.
  3. C. Baier (1998): On Algorithmic Verification Methods for Probabilistic Systems. University of Mannheim. Hablitations Thesis.
  4. C. Baier, H. Hermanns, J.-P. Katoen & V. Wolf (2006): Bisimulation and Simulation Relations for Markov Chains. Electronic Notes in Theoretical Computer Science 162, pp. 73–78, doi:10.1016/j.entcs.2005.12.078.
  5. F. Bartels, A. Sokolova & E.P. de Vink (2004): A hierarchy of probabilistic system types. Theoretical Computer Science 327, pp. 3–22, doi:10.1016/j.tcs.2004.07.019.
  6. M. Bernardo, R. De Nicola & M. Loreti (2013): A uniform framework for modeling nondeterministic, probabilistic, stochastic, or mixed processes and their behavioral equivalences. Information and Computation 225, pp. 29–82, doi:10.1016/j.ic.2013.02.004.
  7. F. Bonchi, M. Bonsangue, M. Boreale, J. Rutten & A. Silva (2012): A coalgebraic perspective on linear weighted automata. Information and Computation 211, pp. 77–105, doi:10.1016/j.ic.2011.12.002.
  8. T. Brengos, M. Miculan & M. Peressotti (2014): Behavioural equivalences for coalgebras with unobservable moves. CoRR abs/1411.0090. Available at
  9. S. Crafa & F. Ranzato (2011): A Spectrum of Behavioral Relations over LTSs on Probability Distributions. In: J.-.P Katoen & B. König: Proc. CONCUR 2011. LNCS 6901, pp. 124–139, doi:10.1007/978-3-642-23217-6_9.
  10. R. De Nicola, D. Latella, M. Loreti & M. Massink (2009): Rate-based Transition Systems for Stochastic Process Calculi. In: S. Albers et al.: Proc. ICALP 2009, Part II. LNCS 5556, pp. 435–446, doi:10.1007/978-3-642-02930-1_36.
  11. R. De Nicola, D. Latella, M. Loreti & M. Massink (2013): A Uniform Definition of Stochastic Process Calculi. ACM Computing Surveys 46, pp. 5:1–5:35, doi:10.1145/2522968.2522973.
  12. C. Eisentraut, H. Hermanns & Lijun Zhang (2010): Concurrency and Composition in a Stochastic World. In: P. Gastin & F. Laroussinie: Proc. CONCUR 2010. LNCS 6269, pp. 21–39, doi:10.1007/978-3-642-15375-4_3.
  13. C. Eisentraut, H. Hermanns & Lijun Zhang (2010): On Probabilistic Automata in Continuous Time. In: Proc. LICS, Edinburgh. IEEE Computer Society, pp. 342–351.
  14. M. Hennessy (2012): Exploring probabilistic bisimulations, part I. Formal Aspects of Computing 24, pp. 749–768, doi:10.1007/s00165-012-0242-7.
  15. H. Hermanns (2002): Interactive Markov Chains: The Quest for Quantified Quality. LNCS 2428, doi:10.1007/3-540-45804-2.
  16. H. Hermanns & J.-P. Katoen (20010): The How and Why of Interactive Markov Chains. In: F.S. de Boer, M.M. Bonsangue, S. Hallerstede & M. Leuschel: Proc. FMCO 2009. LNCS 6286, pp. 311–337, doi:10.1007/978-3-642-17071-3_16.
  17. J. Hillston (1996): A Compositional Approach to Performance Modelling. Distinguished Dissertations in Computer Science 12. Cambridge University Press, doi:10.1017/CBO9780511569951.
  18. B. Klin (2009): Structural Operational Semantics for Weighted Transition Systems. In: J. Palsberg: Semantics and Algebraic Specification. LNCS 5700, pp. 121–139, doi:10.1007/978-3-642-04164-8_7.
  19. B. Klin & V. Sassone (2008): Structural Operational Semantics for Stochastic Process Calculi. In: R.M. Amadio: Proc. FoSSaCS 2008. LNCS 4962, pp. 428–442, doi:10.1007/978-3-540-78499-9_30.
  20. A. Kurz (2000): Logics for coalgebras and applications to computer science. LMU München.
  21. K.G. Larsen & A. Skou (1991): Bisimulation through Probabilistic Testing. Information and Computation 94, pp. 1–28, doi:10.1016/0890-5401(91)90030-6.
  22. D. Latella, M. Massink & E.P. de Vink (2013): Coalgebraic Bisimulation of FuTS. Technical Report TR 09. ASCENS: Autonomic Service-Component Ensembles (EU Proj. 257414).
  23. D. Latella, M. Massink & E.P. de Vink: Bisimulation of Labeled State-to-Function Transition Systems Coalgebraically. Submitted.
  24. D. Latella, M. Massink & E.P. de Vink (2012): Bisimulation of Labeled State-to-Function Transition Systems of Stochastic Process Languages. In: U. Golas & T. Soboll: Proc. ACCAT 2012. EPTSC 93, pp. 23–43, doi:10.4204/EPTCS.93.2.
  25. M. Miculan & M. Peressotti (2013): Weak bisimulations for labelled transition systems weighted over semirings. CoRR abs/1310.4106. Available at
  26. M. Miculan & M. Peressotti (2014): GSOS for non-deterministic processes with quantitative aspects. In: N. Bertrand & L. Bortolussi: Proc. QAPL 2014. EPTCS 154, pp. 17–33, doi:10.4204/EPTCS.154.2.
  27. P. Panangaden (2009): Labelled Markov Processes. Imperial College Press, doi:10.1142/9781848162891.
  28. J.J.M.M. Rutten (2000): Universal coalgebra: a theory of systems. Theoretical Computer Science 249, pp. 3–80, doi:10.1016/S0304-3975(00)00056-6.
  29. R. Segala & N.A. Lynch (1995): Probabilistic Simulations for Probabilistic Processes. Nordic Journal of Computing 2, pp. 250–273.
  30. A. Sokolova (2011): Probabilistic systems coalgebraically: A survey. Theoretical Computer Science 412, pp. 5095–5110, doi:10.1016/j.tcs.2011.05.008.
  31. A. Sokolova, E.P. de Vink & H. Woracek (2009): Coalgebraic Weak Bisimulation for Action-Type Systems. Scientific Annals of Computer Science 19, pp. 93–144.
  32. S. Staton (2011): Relating coalgebraic notions of bisimulation. Logical Methods in Computer Science 7, pp. 1–21, doi:10.2168/LMCS-7(1:13)2011.
  33. M. Timmer, J.-P. Katoen, J. van de Pol & M. Stoelinga (2012): Efficient Modelling and Generation of Markov Automata. In: M. Koutny & I. Ulidowski: Proc. CONCUR 2012. LNCS 7454, pp. 364–379, doi:10.1007/978-3-642-32940-1_26.

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