CFBM - A Framework for Data Driven Approach in Agent-Based Modeling and Simulation

Truong, Thai Minh; Amblard, Frédéric; Gaudou, Benoît; Blanc, Christophe Sibertin

doi:10.1007/978-3-319-46909-6_24

Cited by 5 publications

(3 citation statements)

References 18 publications

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“…The agent might know some "service agents", which provide new functionalities, es. databases as done in Truong et al (2016). Depending on the type of agent, it will have different attributes, it will perform different actions during the time step and it will have different methods for event-based behaviours.…”

Section: Methodsmentioning

confidence: 99%

A hierarchical and modular agent-oriented framework for power systems co-simulations

et al. 2022

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During the last decades, numerous simulation tools have been proposed to faithfully reproduce the different entities of the grid together with the inclusion of new elements that make the grid “smart”. Often, these domain-specific simulators have been then coupled with co-simulation platforms to test new scenarios. In parallel, agent-oriented approaches have been introduced to test distributed control strategies and include social and behavioural aspects typical of the consumer side. Rarely, simulators of the physical systems have been coupled with these innovative techniques, especially when social and psychological aspects have been considered. In order to ease the re-usability of these simulators, avoiding re-coding everything from scratch, we propose a hierarchical and modular agent-oriented framework to test new residential strategies in the energy context. If needed, the presented work enables the user to select the desired level of details of the agent-based framework to match the corresponding physical system without effort to test very different scenarios. Moreover, it allows adding on top of the physical data, behavioural aspects. To this end, the characteristics of the framework are first introduced and then different scenarios are described to demonstrate the flexibility of the proposed work: (i) a first stand-alone scenario with two hierarchy levels, (ii) a second co-simulation scenario with a photovoltaic panel simulator and (iii) a third stand-alone scenario with three hierarchy levels. Results demonstrate the flexibility and ease of use of the framework, allowing us to compare several scenarios and couple new simulators to build a more and more complex environment. The framework is in the early stages of its development. However, thanks to its properties in the future it could be extended to include new actors, such as industries, to get the full picture.

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Section: Methodsmentioning

confidence: 99%

A hierarchical and modular agent-oriented framework for power systems co-simulations

et al. 2022

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“…Truong and his coauthors [19]- [21] proposed a conceptual framework which can be used for simulation models dealing with high volumes of data. The simulation model uses data stored in a DW, combining both real data and simulation data from previously conducted simulation experiment.…”

Section: Simulation and Structures To Store And Integrate Datamentioning

confidence: 99%

On the use of simulation as a Big Data semantic validator for supply chain management

Vieira

Dias

Santos

et al. 2020

Simulation Modelling Practice and Theory

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Simulation stands out as an appropriate method for the Supply Chain Management (SCM) field. Nevertheless, to produce accurate simulations of Supply Chains (SCs), several business processes must be considered. Thus, when using real data in these simulation models, Big Data concepts and technologies become necessary, as the involved data sources generate data at increasing volume, velocity and variety, in what is known as a Big Data context. While developing such solution, several data issues were found, with simulation proving to be more efficient than traditional data profiling techniques in identifying them. Thus, this paper proposes the use of simulation as a semantic validator of the data, proposed a classification for such issues and quantified their impact in the volume of data used in the final achieved solution. This paper concluded that, while SC simulations using Big Data concepts and technologies are within the grasp of organizations, their data models still require considerable improvements, in order to produce perfect mimics of their SCs. In fact, it was also found that simulation can help in identifying and bypassing some of these issues.

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“…Truong and his co-authors (Truong et al 2013;Truong et al 2014;Truong et al 2016) proposed a framework which can be used for simulation models dealing with high volumes of data. The simulation model uses data stored in a DW, which combines real data from the system and also results from previous simulation experiments.…”

Section: Related Workmentioning

confidence: 99%

Real-Time Supply Chain Simulation: A Big Data-Driven Approach

Vieira

Dias

Santos

et al. 2019

2019 Winter Simulation Conference (WSC)

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Simulation of Supply Chains comprises huge amounts of data, resulting in numerous entities flowing in the model. These networks are highly dynamic systems, where entities' relationships and other elements evolve with time, paving the way for real-time Supply Chain decision-support tools capable of using real data. In light of this, a solution comprising of a Big Data Warehouse to store relevant data and a simulation model of an automotive plant, are being developed. The purpose of this paper is to address the modelling approach, which allowed the simulation model to automatically adapt to the data stored in a Big Data Warehouse and thus adapt to new scenarios without manual intervention. The main characteristics of the conceived solution were demonstrated, with emphasis to the real-time and the ability to allow the model to load the state of the system from the Big Data Warehouse.

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CFBM - A Framework for Data Driven Approach in Agent-Based Modeling and Simulation

Cited by 5 publications

References 18 publications

A hierarchical and modular agent-oriented framework for power systems co-simulations

A hierarchical and modular agent-oriented framework for power systems co-simulations

On the use of simulation as a Big Data semantic validator for supply chain management

Real-Time Supply Chain Simulation: A Big Data-Driven Approach

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