Uncertainty on Discrete-Event System Simulation

Uncertainty Propagation methods are well-established when used in modeling and simulation formalisms like differential equations. Nevertheless, until now there are no methods for Discrete-Dynamic Systems. Uncertainty-Aware Discrete-Event System Specification (UA-DEVS) is a formalism for modeling Discrete-Event Dynamic Systems that include uncertainty quantification in messages, states, and event times. UA-DEVS models provide a theoretical framework to describe the models’ uncertainty and their properties. As UA-DEVS models can include continuous variables and non-computable functions, their simulation could be non-computable. For this reason, we also introduce Interval-Approximated Discrete-Event System Specification (IA-DEVS), a formalism that approximates UA-DEVS models using a set of order and bounding functions to obtain a computable model. The computable model approximation produces a tree of all trajectories that can be traversed from the original model and some erroneous ones introduced by the approximation process. We also introduce abstract simulation algorithms for IA-DEVS, present a case study of UA-DEVS, its IA-DEVS approximation and, its simulation results using the algorithms defined.

Computational challenges to test and revitalize Claude Lévi-Strauss transformational methodology

The ambition and proposal for data modeling of myths presented in this paper is to link contemporary technical affordances to some canonical projects developed in structural anthropology. To articulate the theoretical promise and innovation of this proposal, we present a discrete-event system specification modeling and simulation approach in order to perform a generative analysis and a dynamic visualization of selected narratives, aimed at validating and revitalizing the transformational and morphodynamic theory and methodology proposed by Claude Lévi-Strauss in his structural analysis of myth. After an analysis of Lévi-Strauss’s transformational methodology, we describe in detail how discrete-event system specification models are implemented and developed in the framework of a DEVSimPy software environment. The validation of the method involves a discrete-event system specification simulation based on the extension of discrete-event system specification models dedicated to provide a dynamic Google Earth visualization of the selected myth. Future work around the discrete-event system specification formalism in anthropology is described as well as future applications regarding the impact of computational models (discrete-event system specification formalism, Bayesian inferences, and object-oriented features) to new contemporary anthropological domains.

A DSDEVS-Based Model for Verifying Structural Constraints in Dynamic Business Processes

This paper presents a DSDEVS-based model “Dynamic Structure Discrete Event System specification” for modeling and simulating business processes with dynamic structure regarding to different contexts. Consequently, this model, formally, improves the reuse of configurable business processes. Thus, the proposed model allows the analysts to personalize their configurable business processes in a sound manner by verifying a set of structure properties, such as, the lack of synchronization and the deadlock by means of simulation. The implementation was done in DEVS-Suite simulator, which is based on DEVSJAVA models.

Integration of Activity Specification into DEVS Modeling & Simulation Development Environment

We propose an integrative environment for the modeling and simulation of activity specification. The devised approach relies on the DEVS (Discrete Event System Specification) formalism for the foundational semantics of the essential activity elements. The code generation takes place afterward, targeting specific DEVS-compliant modeling and simulation (M\&S) environments such as DEVS-Suite and MS4 Me. The modelers can set parameters or modify the code to satisfy specific needs. The simulation can then be conducted with behavior monitoring and visualization. We demonstrate the approach with observations about performance evaluation and tracking. Such environments have the potential to facilitate computational model development for System of Systems via full-scale simulation support.