Agent-Based and System Dynamics Hybrid Modeling and Simulation Approach Using Systems Modeling Language

Agent-based (AB) and system dynamics (SD) modeling and simulation techniques have been studied and used by various research fields. After the new hybrid modeling field emerged, the combination of these techniques started getting attention in the late 1990\u27s. Applications of using agent-based (AB) and system dynamics (SD) hybrid models for simulating systems have been demonstrated in the literature. However, majority of the work on the domain includes system specific approaches where the models from two techniques are integrated after being independently developed. Existing work on creating an implicit and universal approach is limited to conceptual modeling and structure design. This dissertation proposes an approach for generating AB-SD hybrid models of systems by using Systems Modeling Language (SysML) which can be simulated without exporting to another software platform. Although the approach is demonstrated using IBM\u27s Rational Rhapsody it is applicable to all other SysML platforms. Furthermore, it does not require prior knowledge on agent-based or system dynamics modeling and simulation techniques and limits the use of any programming languages through the use of SysML diagram tools. The iterative modeling approach allows two-step validations, allows establishing a two-way dynamic communication between AB and SD variables and develops independent behavior models that can be reused in representing different systems. The proposed approach is demonstrated using a hypothetical population, movie theater and a real–world training management scenarios. In this setting, the work provides methods for independent behavior and system structure modeling. Finally, provides behavior models for probabilistic behavior modeling and time synchronization

Multi-Agent Systems

A multi-agent system (MAS) is a system composed of multiple interacting intelligent agents. Multi-agent systems can be used to solve problems which are difficult or impossible for an individual agent or monolithic system to solve. Agent systems are open and extensible systems that allow for the deployment of autonomous and proactive software components. Multi-agent systems have been brought up and used in several application domains

A holistic model of emergency evacuations in large, complex, public occupancy buildings

Evacuations are crucial for ensuring the safety of building occupants in the event of an emergency. In large, complex, public occupancy buildings (LCPOBs) these procedures are significantly more complex than the simple withdrawal of people from a building. This thesis has developed a novel, holistic, theoretical model of emergency evacuations in LCPOBs inspired by systems safety theory. LCPOBs are integral components of complex socio-technical systems, and therefore the model describes emergency evacuations as control actions initiated in order to return the building from an unsafe state to a safe state where occupants are not at risk of harm. The emergency evacuation process itself is comprised of four aspects - the movement (of building occupants), planning and management, environmental features, and evacuee behaviour. To demonstrate its utility and applicability, the model has been employed to examine various aspects of evacuation procedures in two example LCPOBs - airport terminals, and sports stadiums. The types of emergency events initiating evacuations in these buildings were identified through a novel hazard analysis procedure, which utilised online news articles to create events databases of previous evacuations. Security and terrorism events, false alarms, and fires were found to be the most common cause of evacuations in these buildings. The management of evacuations was explored through model-based systems engineering techniques, which identified the communication methods and responsibilities of staff members managing these events. Social media posts for an active shooting event were analysed using qualitative and machine learning methods to determine their utility for situational awareness. This data source is likely not informative for this purpose, as few posts detail occupant behaviours. Finally, an experimental study on pedestrian dynamics with movement devices was conducted, which determined that walking speeds during evacuations were unaffected by evacuees dragging luggage, but those pushing pushchairs and wheelchairs will walk significantly slower.Open Acces

A model-based approach to System of Systems risk management

The failure of many System of Systems (SoS) enterprises can be attributed to the inappropriate application of traditional Systems Engineering (SE) processes within the SoS domain, because of the mistaken belief that a SoS can be regarded as a single large, or complex, system. SoS Engineering (SoSE) is a sub-discipline of SE; Risk Management and Modelling and Simulation (M&S) are key areas within SoSE, both of which also lie within the traditional SE domain. Risk Management of SoS requires a different approach to that currently taken for individual systems; if risk is managed for each component system then it cannot be assumed that the aggregated affect will be to mitigate risk at the SoS level. A literature review was undertaken examining three themes: (1) SoS Engineering (SoSE), (2) M&S and (3) Risk. Theme 1 of the literature provided insight into the activities comprising SoSE and its difference from traditional SE with risk management identified as a key activity. The second theme discussed the application of M&S to SoS, providing an output, which supported the identification of appropriate techniques and concluding that, the inherent complexity of a SoS required the use of M&S in order to support SoSE activities. Current risk management approaches were reviewed in theme 3 as well as the management of SoS risk. Although some specific examples of the management of SoS risk were found, no mature, general approach was identified, indicating a gap in current knowledge. However, it was noted most of these examples were underpinned by M&S approaches. It was therefore concluded a general approach SoS risk management utilising M&S methods would be of benefit. In order to fill the gap identified in current knowledge, this research proposed a new model based approach to Risk Management where risk identification was supported by a framework, which combined SoS system of interest dimensions with holistic risk types, where the resulting risks and contributing factors are captured in a causal network. Analysis of the causal network using a model technique selection tool, developed as part of this research, allowed the causal network to be simplified through the replacement of groups of elements within the network by appropriate supporting models. The Bayesian Belief Network (BBN) was identified as a suitable method to represent SoS risk. Supporting models run in Monte Carlo Simulations allowed data to be generated from which the risk BBNs could learn, thereby providing a more quantitative approach to SoS risk management. A method was developed which provided context to the BBN risk output through comparison with worst and best-case risk probabilities. The model based approach to Risk Management was applied to two very different case studies: Close Air Support mission planning and the Wheat Supply Chain, UK National Food Security risks, demonstrating its effectiveness and adaptability. The research established that the SoS SoI is essential for effective SoS risk identification and analysis of risk transfer, effective SoS modelling requires a range of techniques where suitability is determined by the problem context, the responsibility for SoS Risk Management is related to the overall SoS classification and the model based approach to SoS risk management was effective for both application case studies

Proceedings, MSVSCC 2011

Proceedings of the 5th Annual Modeling, Simulation & Visualization Student Capstone Conference held on April 14, 2011 at VMASC in Suffolk, Virginia. 186 pp

Modélisation de Systèmes Complexes par Composition : Une démarche hiérarchique pour la co-simulation de composants hétérogènes

This work deals with complex system Modeling and Simulation (M&S). The particularity of such systems is the numerous heterogeneous entities in interaction involved inside them. This particularity leads to several organization layers and scientific domains. As a consequence, their study requests many perspectives (different temporal and spatial scales, different domains and formalisms, different granularities...). The challenge is the rigorous integration of these various system perspectives inside an M&S process. In other words, the difficulty is to define successive steps to follow in order to integrate several points of view inside the same model. Multi-modeling and co-simulation are promising approaches to do so. The underlying problem is to define a modular and hierarchical process fitted with a rigorous way to integrate heterogeneous components and which is supported by a software environment that covers the whole M&S cycle.MECSYCO (Multi-agent Environment for Complex SYstem CO-simulation) is a co-simulation middleware focusing on the reuse of existing models from other software. It relies on a software and formal DEVS-based wrapping, provides heterogeneity handling mechanisms and ensures a decentralized and modular co-simulation. MECSYCO deals with the heterogeneous component integration need but its M&S process does not have all the properties above-mentioned. Notably, the hierarchical modeling ability is missing.To overcome this, we propose to fit MECSYCO with a descriptive multi-modeling and co-simulation process that allows the hierarchical design of multi-models using models from other software. Our process is split into three steps: the atomic model integration, the composition (hierarchical multi-model construction) and finally the experimentation. We adopt a descriptive approach where a description file is linked to each product of these steps, these documents enable to manipulate them.The use of description files completes the integration steps, allows a hierarchical and modular multi-model design and isolates the experiments.Then we set up a development environment based on Domain Specific Languages (DSL) to support the description work, and we automate the transition from an experiment description to its effective co-simulation. This is a Model-Driven Engineering approach which allows us to put into practice our contribution by facilitating the modelers' work and by avoiding implementation mistakes.Our contribution fits MECSYCO with the hierarchical design property and with a DSL-based M&S environment while keeping its rigorous integration process and its modularity. Our work is evaluated on two examples. The first one renews a hybrid highway multi-model already implemented in MECSYCO, it shows the conservation of the middleware former properties. The second one is a simple thermal smart-building multi-model which highlights the incremental design of a multi-model and the integration of new components while putting our entire approach into practice.Le contexte de ce travail est la modélisation et simulation (M&S) de systèmes complexes. Ces systèmes se caractérisent par un grand nombre d'entités hétérogènes en interaction faisant apparaitre plusieurs niveaux d'organisation et plusieurs domaines. Leur étude nécessite de combiner plusieurs points de vue (différentes échelles temporelles et spatiales, différents domaines scientifiques et formalismes, différents niveaux de résolution...).Le challenge est l'intégration rigoureuse de ces différents points de vue sur un système au sein d'une démarche de M&S. Dit autrement, le défi est de définir une marche à suivre permettant d'intégrer plusieurs perspectives au sein d'un même modèle. La multi-modélisation et la co-simulation sont deux approches prometteuses pour cela. La difficulté sous-jacente est de fournir une démarche de M&S modulaire, hiérarchique, dotée d'une approche d'intégration de composants hétérogènes rigoureuse et associée à un environnement logiciel supportant l'ensemble du cycle de M&S pour la mettre en pratique.MECSYCO (Multi-agent Environment for Complex SYstem CO-simulation) est un intergiciel de co-simulation se focalisant sur la réutilisation de modèles issus d'autres logiciels. Il se base sur une stratégie d'encapsulation logicielle et formelle fondée sur DEVS, fournit des mécanismes de gestion des hétérogénéités, et assure une co-simulation décentralisée et modulaire. MECSYCO répond au besoin d'intégration de composants hétérogènes au sein d'une co-simulation, mais ne propose pas de démarche complète comprenant l'ensemble des propriétés énoncées précédemment. Il manque notamment la possibilité de hiérarchiser. Pour pallier à ce manque, dans la continuité des travaux sur MECSYCO nous proposons une démarche de multi-modélisation et co-simulation descriptive autorisant la construction incrémentale de multi-modèles à partir de modèles issus d'autres logiciels. Notre démarche est décomposée en trois étapes : l'intégration des modèles atomiques, la composition (création hiérarchique du multi-modèle) et enfin l'expérimentation. Nous adoptons une approche descriptive où chaque élément produit lors de ces étapes est associé à une description permettant de le manipuler. L'utilisation des descriptions complète le processus d'intégration, permet la construction incrémentale et modulaire des multi-modèles, et isole l'expérimentation. Nous mettons ensuite en place un environnement de développement basé sur des langages dédiés aux descriptions, et nous automatisons le passage d'une description d'expérience à sa co-simulation effective. C'est une démarche d'Ingénierie Dirigée par les Modèles qui nous permet de mettre en pratique notre approche en facilitant le travail des modélisateurs et en évitant les erreurs d'implémentation.Nous apportons à MECSYCO la propriété de hiérarchisation et un environnement de développement tout en conservant l'intégration rigoureuse et la modularité. Nous évaluons notre contribution sur deux exemples. Le premier reprend un multi-modèle d'autoroute hybride implémenté dans MECSYCO, il montre la conservation des propriétés d'intégration. Le second est un multi-modèle simple de thermique de bâtiment intelligent, il illustre la construction incrémentale d'un multi-modèle et l'intégration de nouveaux composants tout en mettant en pratique l'ensemble de notre démarche

Proceedings, MSVSCC 2012

Proceedings of the 6th Annual Modeling, Simulation & Visualization Student Capstone Conference held on April 19, 2012 at VMASC in Suffolk, Virginia

XXIII Congreso Argentino de Ciencias de la Computación - CACIC 2017 : Libro de actas

Trabajos presentados en el XXIII Congreso Argentino de Ciencias de la Computación (CACIC), celebrado en la ciudad de La Plata los días 9 al 13 de octubre de 2017, organizado por la Red de Universidades con Carreras en Informática (RedUNCI) y la Facultad de Informática de la Universidad Nacional de La Plata (UNLP).Red de Universidades con Carreras en Informática (RedUNCI