Bisimulation and cocongruence for probabilistic systems

نویسندگان

  • Vincent Danos
  • Josée Desharnais
  • François Laviolette
  • Prakash Panangaden
چکیده

We introduce a new notion of bisimulation, called event bisimulation on labelled Markov processes (LMPs) and compare it with the, now standard, notion of probabilistic bisimulation, originally due to Larsen and Skou. Event bisimulation uses a sub σ-algebra as the basic carrier of information rather than an equivalence relation. The resulting notion is thus based on measurable subsets rather than on points: hence the name. Event bisimulation applies smoothly for general measure spaces; bisimulation, on the other hand, is known only to work satisfactorily for analytic spaces. We prove the logical characterization theorem for event bisimulation without having to invoke any of the subtle aspects of analytic spaces that feature prominently in the corresponding proof for ordinary bisimulation. These complexities only arise when we show that on analytic spaces the two concepts co-incide. We show that the concept of event bisimulation arises naturally from taking the co-congruence point of view for probabilistic systems. We show that the theory can be given a pleasing categorical treatment in line with general coalgebraic principles. As an easy application of these ideas we develop a notion of “almost sure” bisimulation; the theory comes almost “for free” once we modify Giry’s monad appropriately.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Bisimulation for BL-general fuzzy automata

In this note, we define bisimulation for BL-general fuzzy automata and show that if there is a bisimulation between two BL-general fuzzy automata, then they have the same behavior.For a given BL-general fuzzy automata, we obtain the greatest bisimulation for the BL-general fuzzy automata. Thereafter, if we use the greatest bisimulation, then we obtain a quotient BL-general fuzzy automata and th...

متن کامل

Polynomial Time Algorithms for Testing Probabilistic Bisimulation and Simulation

Various models and equivalence relations or preorders for probabilistic processes are proposed in the literature. This paper deals with a model based on labelled transition systems extended to the prob-abalistic setting and gives an O(n 2 m) algorithm for testing probabilistic bisimulation and an O(n 5 m 2) algorithm for testing probabilistic simulation where n is the number of states and m the...

متن کامل

Weak Bisimulation for Fully Probabilistic Processes

Bisimulations that abstract from internal computation have proven to be useful for verification of compositionally defined transition systems. In the literature of probabilistic extensions of such transition systems, similar bisimulations are rare. In this paper, we introduce weak and branching bisimulation for fully probabilistic systems, transition systems where nondeterministic branching is ...

متن کامل

Bisimulation on Markov Processes over Arbitrary Measurable Spaces

We introduce a notion of bisimulation on labelled Markov Processes over generic measurable spaces in terms of arbitrary binary relations. Our notion of bisimulation is proven to coincide with the coalgebraic definition of Aczel and Mendler in terms of the Giry functor, which associates with a measurable space its collection of (sub)probability measures. This coalgebraic formulation allows one t...

متن کامل

Decision Algorithms for Probabilistic Bisimulation

We propose decision algorithms for bisimulation relations defined on probabilistic automata, a model for concurrent nondeterministic systems with randomization. The algorithms decide both strong and weak bisimulation relations based on deterministic as well as randomized schedulers. These algorithms extend and complete other known algorithms for simpler relations and models. The algorithm we pr...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:
  • Inf. Comput.

دوره 204  شماره 

صفحات  -

تاریخ انتشار 2006