scholarly journals Agent-based simulation modelling for regional ecological-economic systems. A case study of the Republic of Armenia

2016 ◽  
Vol 2 (1) ◽  
pp. 104-115 ◽  
Author(s):  
L.A. Beklaryan ◽  
2021 ◽  
Vol 12 (1) ◽  
pp. 18
Author(s):  
Lennart Adenaw ◽  
Markus Lienkamp

In order to electrify the transport sector, scores of charging stations are needed to incentivize people to buy electric vehicles. In urban areas with a high charging demand and little space, decision-makers are in need of planning tools that enable them to efficiently allocate financial and organizational resources to the promotion of electromobility. As with many other city planning tasks, simulations foster successful decision-making. This article presents a novel agent-based simulation framework for urban electromobility aimed at the analysis of charging station utilization and user behavior. The approach presented here employs a novel co-evolutionary learning model for adaptive charging behavior. The simulation framework is tested and verified by means of a case study conducted in the city of Munich. The case study shows that the presented approach realistically reproduces charging behavior and spatio-temporal charger utilization.


2020 ◽  
pp. 369-389
Author(s):  
Sara Montagna ◽  
Andrea Omicini

This chapter aims at discussing the content of multi-agent based simulation (MABS) applied to computational biology i.e., to modelling and simulating biological systems by means of computational models, methodologies, and frameworks. In particular, the adoption of agent-based modelling (ABM) in the field of multicellular systems biology is explored, focussing on the challenging scenarios of developmental biology. After motivating why agent-based abstractions are critical in representing multicellular systems behaviour, MABS is discussed as the source of the most natural and appropriate mechanism for analysing the self-organising behaviour of systems of cells. As a case study, an application of MABS to the development of Drosophila Melanogaster is finally presented, which exploits the ALCHEMIST platform for agent-based simulation.


2019 ◽  
Vol 41 ◽  
pp. 295-308
Author(s):  
Thorsten Neumann ◽  
Matthias Heinrichs ◽  
Michael Behrisch ◽  
Jakob Erdmann ◽  
Anke Sauerländer-Biebl

PLoS ONE ◽  
2015 ◽  
Vol 10 (3) ◽  
pp. e0118359 ◽  
Author(s):  
Grazziela P. Figueredo ◽  
Peer-Olaf Siebers ◽  
Uwe Aickelin ◽  
Amanda Whitbrook ◽  
Jonathan M. Garibaldi

2017 ◽  
Vol 346 ◽  
pp. 99-118 ◽  
Author(s):  
Andranik S. Akopov ◽  
Levon A. Beklaryan ◽  
Armen K. Saghatelyan

Sign in / Sign up

Export Citation Format

Share Document