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Keywords = bisimulation

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31 pages, 456 KiB  
Article
Safety of Uncertain Session Types with Interval Probability
by Bogdan Aman and Gabriel Ciobanu
Symmetry 2025, 17(2), 218; https://doi.org/10.3390/sym17020218 - 1 Feb 2025
Viewed by 485
Abstract
In this article, we introduce and study a new kind of multiparty session type for a probabilistic process calculus that incorporates two forms of choice: probabilistic and nondeterministic. The main novelty of our approach is the use of interval probabilities in a type [...] Read more.
In this article, we introduce and study a new kind of multiparty session type for a probabilistic process calculus that incorporates two forms of choice: probabilistic and nondeterministic. The main novelty of our approach is the use of interval probabilities in a type system in order to deal with uncertainty in a probabilistic process calculus. We present a decidable proof system that ensures deadlock freedom, type preservation and type safety, even when several types can be assigned to a process. The new typing system represents a conservative extension of the standard typing system based on multiparty session types (removing the probabilities from processes does not affect their well-typedness). We also define a probabilistic bisimulation between processes that are typed by using the same sorting and typing. Full article
(This article belongs to the Section Mathematics)
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19 pages, 2188 KiB  
Article
Simultaneous Method for Solving Certain Systems of Matrix Equations with Two Unknowns
by Predrag S. Stanimirović, Miroslav Ćirić, Spyridon D. Mourtas, Gradimir V. Milovanović and Milena J. Petrović
Axioms 2024, 13(12), 838; https://doi.org/10.3390/axioms13120838 - 28 Nov 2024
Viewed by 926
Abstract
Quantitative bisimulations between weighted finite automata are defined as solutions of certain systems of matrix-vector inequalities and equations. In the context of fuzzy automata and max-plus automata, testing the existence of bisimulations and their computing are performed through a sequence of matrices that [...] Read more.
Quantitative bisimulations between weighted finite automata are defined as solutions of certain systems of matrix-vector inequalities and equations. In the context of fuzzy automata and max-plus automata, testing the existence of bisimulations and their computing are performed through a sequence of matrices that is built member by member, whereby the next member of the sequence is obtained by solving a particular system of linear matrix-vector inequalities and equations in which the previously computed member appears. By modifying the systems that define bisimulations, systems of matrix-vector inequalities and equations with k unknowns are obtained. Solutions of such systems, in the case of existence, witness to the existence of a certain type of partial equivalence, where it is not required that the word functions computed by two WFAs match on all input words, but only on all input words whose lengths do not exceed k. Solutions of these new systems represent finite sequences of matrices which, in the context of fuzzy automata and max-plus automata, are also computed sequentially, member by member. Here we deal with those systems in the context of WFAs over the field of real numbers and propose a different approach, where all members of the sequence are computed simultaneously. More precisely, we apply a simultaneous approach in solving the corresponding systems of matrix-vector equations with two unknowns. Zeroing neural network (ZNN) neuro-dynamical systems for approximating solutions of heterotypic bisimulations are proposed. Numerical simulations are performed for various random initial states and comparison with the Matlab, linear programming solver linprog, and the pseudoinverse solution generated by the standard function pinv is given. Full article
(This article belongs to the Special Issue Numerical Analysis and Optimization)
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32 pages, 616 KiB  
Article
Program Equivalence in the Erlang Actor Model
by Péter Bereczky, Dániel Horpácsi and Simon Thompson
Computers 2024, 13(11), 276; https://doi.org/10.3390/computers13110276 - 23 Oct 2024
Viewed by 1074
Abstract
This paper presents the formal semantics of concurrency in Core Erlang, an intermediate language for Erlang, along with a notion of program equivalence (based on barbed bisimulation) that is able to model equivalence between programs that have different communication structures but the same [...] Read more.
This paper presents the formal semantics of concurrency in Core Erlang, an intermediate language for Erlang, along with a notion of program equivalence (based on barbed bisimulation) that is able to model equivalence between programs that have different communication structures but the same observable behaviour. The novelty in our formalisation is its extent: it includes semantics for messages and exit and link signals, in addition to most of Core Erlang’s sequential features. Furthermore, unlike previous studies, this work formalises message receipt using primitive operations, consistent with the standard as of Erlang/OTP 23. In this novel formalisation, we show some generally applicable program equivalences (such as process identifier renaming and silent evaluation) and present a practical case study featuring the equivalence of sequential and concurrent list processing. Full article
(This article belongs to the Special Issue Best Practices, Challenges and Opportunities in Software Engineering)
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26 pages, 2071 KiB  
Article
Simulations and Bisimulations between Weighted Finite Automata Based on Time-Varying Models over Real Numbers
by Predrag S. Stanimirović, Miroslav Ćirić, Spyridon D. Mourtas, Pavle Brzaković and Darjan Karabašević
Mathematics 2024, 12(13), 2110; https://doi.org/10.3390/math12132110 - 5 Jul 2024
Cited by 1 | Viewed by 1269
Abstract
The zeroing neural network (ZNN) is an important kind of continuous-time recurrent neural network (RNN). Meanwhile, the existence of forward and backward simulations and bisimulations for weighted finite automata (WFA) over the field of real numbers has been widely investigated. Two types of [...] Read more.
The zeroing neural network (ZNN) is an important kind of continuous-time recurrent neural network (RNN). Meanwhile, the existence of forward and backward simulations and bisimulations for weighted finite automata (WFA) over the field of real numbers has been widely investigated. Two types of quantitative simulations and two types of bisimulations between WFA are determined as solutions to particular systems of matrix and vector inequations over the field of real numbers R. The approach used in this research is unique and based on the application of a ZNN dynamical evolution in solving underlying matrix and vector inequations. This research is aimed at the development and analysis of four novel ZNN dynamical systems for addressing the systems of matrix and/or vector inequalities involved in simulations and bisimulations between WFA. The problem considered in this paper requires solving a system of two vector inequations and a couple of matrix inequations. Using positive slack matrices, required matrix and vector inequations are transformed into corresponding equations and then the derived system of matrix and vector equations is transformed into a system of linear equations utilizing vectorization and the Kronecker product. The solution to the ZNN dynamics is defined using the pseudoinverse solution of the generated linear system. A detailed convergence analysis of the proposed ZNN dynamics is presented. Numerical examples are performed under different initial state matrices. A comparison between the ZNN and linear programming (LP) approach is presented. Full article
(This article belongs to the Special Issue Advances in Fuzzy Logic and Artificial Neural Networks)
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15 pages, 2977 KiB  
Article
Learning State-Specific Action Masks for Reinforcement Learning
by Ziyi Wang, Xinran Li, Luoyang Sun, Haifeng Zhang, Hualin Liu and Jun Wang
Algorithms 2024, 17(2), 60; https://doi.org/10.3390/a17020060 - 30 Jan 2024
Cited by 3 | Viewed by 4376
Abstract
Efficient yet sufficient exploration remains a critical challenge in reinforcement learning (RL), especially for Markov Decision Processes (MDPs) with vast action spaces. Previous approaches have commonly involved projecting the original action space into a latent space or employing environmental action masks to reduce [...] Read more.
Efficient yet sufficient exploration remains a critical challenge in reinforcement learning (RL), especially for Markov Decision Processes (MDPs) with vast action spaces. Previous approaches have commonly involved projecting the original action space into a latent space or employing environmental action masks to reduce the action possibilities. Nevertheless, these methods often lack interpretability or rely on expert knowledge. In this study, we introduce a novel method for automatically reducing the action space in environments with discrete action spaces while preserving interpretability. The proposed approach learns state-specific masks with a dual purpose: (1) eliminating actions with minimal influence on the MDP and (2) aggregating actions with identical behavioral consequences within the MDP. Specifically, we introduce a novel concept called Bisimulation Metrics on Actions by States (BMAS) to quantify the behavioral consequences of actions within the MDP and design a dedicated mask model to ensure their binary nature. Crucially, we present a practical learning procedure for training the mask model, leveraging transition data collected by any RL policy. Our method is designed to be plug-and-play and adaptable to all RL policies, and to validate its effectiveness, an integration into two prominent RL algorithms, DQN and PPO, is performed. Experimental results obtained from Maze, Atari, and μRTS2 reveal a substantial acceleration in the RL learning process and noteworthy performance improvements facilitated by the introduced approach. Full article
(This article belongs to the Section Algorithms for Multidisciplinary Applications)
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21 pages, 440 KiB  
Article
Fuzzy Automata as Coalgebras
by Ai Liu, Shun Wang, Luis Soares Barbosa and Meng Sun
Mathematics 2021, 9(3), 272; https://doi.org/10.3390/math9030272 - 29 Jan 2021
Cited by 3 | Viewed by 2918
Abstract
The coalgebraic method is of great significance to research in process algebra, modal logic, object-oriented design and component-based software engineering. In recent years, fuzzy control has been widely used in many fields, such as handwriting recognition and the control of robots or air [...] Read more.
The coalgebraic method is of great significance to research in process algebra, modal logic, object-oriented design and component-based software engineering. In recent years, fuzzy control has been widely used in many fields, such as handwriting recognition and the control of robots or air conditioners. It is then an interesting topic to analyze the behavior of fuzzy automata from a coalgebraic point of view. This paper models different types of fuzzy automata as coalgebras with a monad structure capturing fuzzy behavior. Based on the coalgebraic models, we can define a notion of fuzzy language and consider several versions of bisimulation for fuzzy automata. A group of combinators is defined to compose fuzzy automata of two branches: state transition and output function. A case study illustrates the coalgebraic models proposed and their composition. Full article
(This article belongs to the Special Issue Mathematics in Software Reliability and Quality Assurance)
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17 pages, 462 KiB  
Article
Bisimulation for Secure Information Flow Analysis of Multi-Threaded Programs
by Ali A. Noroozi, Jaber Karimpour and Ayaz Isazadeh
Math. Comput. Appl. 2019, 24(2), 64; https://doi.org/10.3390/mca24020064 - 17 Jun 2019
Cited by 5 | Viewed by 3657
Abstract
Preserving the confidentiality of information is a growing concern in software development. Secure information flow is intended to maintain the confidentiality of sensitive information by preventing them from flowing to attackers. This paper discusses how to ensure confidentiality for multi-threaded programs through a [...] Read more.
Preserving the confidentiality of information is a growing concern in software development. Secure information flow is intended to maintain the confidentiality of sensitive information by preventing them from flowing to attackers. This paper discusses how to ensure confidentiality for multi-threaded programs through a property called observational determinism. Operational semantics of multi-threaded programs are modeled using Kripke structures. Observational determinism is formalized in terms of divergence weak low-bisimulation. Bisimulation is an equivalence relation associating executions that simulate each other. The new property is called bisimulation-based observational determinism. Furthermore, a model checking method is proposed to verify the new property and ensure that secure information flow holds in a multi-threaded program. The model checking method successively refines the Kripke model of the program until the quotient of the model with respect to divergence weak low-bisimulation is reached. Then, bisimulation-based observational determinism is checked on the quotient, which is a minimized model of the concrete Kripke model. The time complexity of the proposed method is polynomial in the size of the Kripke model. The proposed approach has been implemented on top of PRISM, a probabilistic model checking tool. Finally, a case study is discussed to show the applicability of the proposed approach. Full article
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22 pages, 920 KiB  
Article
An Efficient Algorithm to Determine Probabilistic Bisimulation
by Jan Friso Groote, Jao Rivera Verduzco and Erik P. De Vink
Algorithms 2018, 11(9), 131; https://doi.org/10.3390/a11090131 - 3 Sep 2018
Cited by 18 | Viewed by 4584
Abstract
We provide an algorithm to efficiently compute bisimulation for probabilistic labeled transition systems, featuring non-deterministic choice as well as discrete probabilistic choice. The algorithm is linear in the number of transitions and logarithmic in the number of states, distinguishing both action states and [...] Read more.
We provide an algorithm to efficiently compute bisimulation for probabilistic labeled transition systems, featuring non-deterministic choice as well as discrete probabilistic choice. The algorithm is linear in the number of transitions and logarithmic in the number of states, distinguishing both action states and probabilistic states, and the transitions between them. The algorithm improves upon the proposed complexity bounds of the best algorithm addressing the same purpose so far by Baier, Engelen and Majster-Cederbaum (Journal of Computer and System Sciences 60:187–231, 2000). In addition, experimentally, on various benchmarks, our algorithm performs rather well; even on relatively small transition systems, a performance gain of a factor 10,000 can be achieved. Full article
(This article belongs to the Special Issue Bisimulation and Simulation Algorithms)
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23 pages, 3873 KiB  
Article
Formal Analysis and Design of Supervisor and User Interface Allowing for Non-Deterministic Choices Using Weak Bi-Simulation
by Shazada Muhammad Umair Khan and Wenlong He
Appl. Sci. 2018, 8(2), 221; https://doi.org/10.3390/app8020221 - 31 Jan 2018
Cited by 5 | Viewed by 3660
Abstract
In human machine systems, a user display should contain sufficient information to encapsulate expressive and normative human operator behavior. Failure in such system that is commanded by supervisor can be difficult to anticipate because of unexpected interactions between the different users and machines. [...] Read more.
In human machine systems, a user display should contain sufficient information to encapsulate expressive and normative human operator behavior. Failure in such system that is commanded by supervisor can be difficult to anticipate because of unexpected interactions between the different users and machines. Currently, most interfaces have non-deterministic choices at state of machine. Inspired by the theories of single user of an interface established on discrete event system, we present a formal model of multiple users, multiple machines, a supervisor and a supervisor machine. The syntax and semantics of these models are based on the system specification using timed automata that adheres to desirable specification properties conducive to solving the non-deterministic choices for usability properties of the supervisor and user interface. Further, the succinct interface developed by applying the weak bi-simulation relation, where large classes of potentially equivalent states are refined into a smaller one, enables the supervisor and user to perform specified task correctly. Finally, the proposed approach is applied to a model of a manufacturing system with several users interacting with their machines, a supervisor with several users and a supervisor with a supervisor machine to illustrate the design procedure of human–machine systems. The formal specification is validated by z-eves toolset. Full article
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