Discrete event modeling and simulation and reinforcement learning are two frameworks suited for cyberphysical system design, which, when combined, can give powerful tools for system optimization or decision making process for example. This paper describes how discrete event modeling and simulation could be integrated into reinforcement learning concepts and tools in order to assist in the realization of reinforcement learning systems, more specially considering the temporal, hierarchical, and multi-agent aspects. An overview of these different improvements are given based on the implementation of the Q-Learning reinforcement learning algorithm in the framework of the Discrete Event system Specification (DEVS) and System Entity Structure (SES) formalisms.

This paper presents a modeling and simulation approach in order to perform a generative analysis of folktales aimed at validating Claude Lévi-Strauss’ theory and method. To this aim, a discrete-event simulation is proposed. The simulation is based on the development of a set of discrete-event models dedicated to generating a set of folktales from an initial one, according to Claude Lévi-Strauss’ structural analysis based on symmetry and double twist transformations. This paper describes in detail how these discrete-event models have been implemented in the framework of the DEVSimPy software environment by using myths of Native American mythology and folktales of Corsican oral literature. The validation involved the following steps: (i) definition of a reference folktale (according to Claude Lévi-Strauss’ methodology) (ii) generation of a set of folktales by performing their own transformations (iii) generation of a graph allowing to analyze the links that have been created after performing a set of folktales transformations. Finally, the computational validation of Lévi-Strauss’s method is intended to ground a new research that may reformulate structural analysis and elaborate a neo-structural model of canonical formalization based on transformational morphodynamics. The aim is to conceptualize and measure recursively the structural dynamics and the recurrent patterns of current identity transformations in liberal democracies, especially in US and EU contexts where ethnic/racial divisions and migration challenges are becoming more acute than ever.

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.

Simulation-based development is a structured approach that uses formal models to design and test system behavior before building the actual system. The Internet of Things (IoT) connects physical devices equipped with sensors and software to collect and exchange data. Cyber-Physical Systems (CPSs) integrate computing directly into physical processes to enable real-time control. This paper reviews the Discrete-Event System Specification (DEVS) formalism and explores how it can serve as a unified framework for designing, simulating, and implementing systems that combine IoT and CPS—referred to as the Internet of Cyber-Things (IoCT). Through case studies that include home automation, solar energy monitoring, conflict management, and swarm robotics, the paper reviews how DEVS enables construction of modular, scalable, and reusable models. The role of the System Entity Structure (SES) is also discussed, highlighting its contribution in organizing models and generating alternative system configurations. With this background as basis, the paper evaluates whether DEVS provides the necessary modeling power and continuity across stages to support the development of complex IoCT systems. The paper concludes that DEVS offers a robust and flexible foundation for developing IoCT systems, supporting both expressiveness and seamless transition from design to real-world deployment.

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