A Formal Model of Patrolling Game and its Agent-Based Simulation Using Jason

2017 ◽  
Author(s):  
Amelia Badica ◽  
Costin Badica ◽  
Catalina Sitnikov ◽  
Florin Leon
Keyword(s):  
Formal Model ◽  
Agent Based Simulation ◽  
Agent Based ◽  
Patrolling Game

scholarly journals A REVIEW OF APPROACHES AND TOOLS FOR COLLABORATIVE NETWORKS SIMULATION

2016 ◽  
Vol 13 (3) ◽  
pp. 232
Author(s):  
Beatriz Andres ◽  
Raul Poler
Keyword(s):  
System Dynamics ◽  
Formal Model ◽  
Simulation System ◽  
Collaborative Networks ◽  
Simulation Approach ◽  
Discrete Events ◽  
Agent Based Simulation ◽  
Agent Based ◽  
Supporting Tool ◽  
Modelling Process

Abstract. Collaborative networks (CN) are characterised by being complex systems, highlighting the need of considering simulation approaches to support the resolution of CN models. Simulation approaches are seen as a supporting tool to analyse the formal model of a supply network. Three relevant simulation approaches are identified for its application in the context of CN models: Discrete Events Simulation, System Dynamics and Agent Based Simulation. Each simulation approach is briefly described and compared with each other, according to a group of relevant features, with the main aim of aiding the modellers in the task of selecting the most appropriate simulation approach to address the modelling process in the context of CN. Besides, a group of commercial and academic tools are listed for each simulation approach.

scholarly journals Multi-Criteria, Co-Evolutionary Charging Behavior: An Agent-Based Simulation of Urban Electromobility

2021 ◽  
Vol 12 (1) ◽  
pp. 18
Author(s):  
Lennart Adenaw ◽  
Markus Lienkamp
Keyword(s):  
Urban Areas ◽  
City Planning ◽  
User Behavior ◽  
Transport Sector ◽  
Simulation Framework ◽  
Agent Based Simulation ◽  
Agent Based ◽  
Charging Station ◽  
Spatio Temporal

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.

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