Seminario Synergia
Bridging Causal Reversibility and Time Reversibility: A Stochastic Process Algebraic Approach
Abstract: Causal reversibility blends causality and reversibility for concurrent systems. It indicates that an action can be undone provided that all of its consequences have been undone already, thus making it possible to bring the system back to a past consistent state. Time reversibility is instead considered in the field of stochastic processes, mostly for efficient analysis purposes. A performance model based on a continuous-time Markov chain is time reversible if its stochastic behavior remains the same when the direction of time is reversed. We bridge these two theories of reversibility by showing the conditions under which causal reversibility and time reversibility are both ensured by construction. This is done in the setting of a stochastic process calculus, which is then equipped with a variant of stochastic bisimilarity accounting for both forward and backward directions. We also investigate the different compositionality properties and axiomatizations of forward bisimilarity, backward bisimilarity, and forward-backward bisimilarity.
Per informazioni: pierluigi.graziani@uniurb.it
Synergia web page: https://sites.google.com/a/uniurb.it/synergia/home
Modalità di partecipazione
- in presenza presso l'aula Turing, Collegio Raffaello, Piazza della Repubblica, n. 13, Urbino,
- online via Link Zoom: https://uniurb-it.zoom.us/j/84849439028?pwd=a2Z1THl5VGh6elk4ZTRHOGd4L1JEUT09
Dettagli sull'evento
Organizzato da Dipartimento di Scienze Pure e Applicate, Gruppo di Ricerca Synergia
Data e luogo
Data inizio: 26/01/2023
alle ore 17:00
Data fine: 26/01/2023
alle ore 19:00
Collegio Raffaello (Urbino, Piazza della Repubblica, 13) Aula Turing
Relatori
Marco Bernardo, Università degli Studi di Urbino Carlo Bo
