A Versatile Multi-Agent Traffic Simulator Framework Based on Real Data

2016 ◽  
Vol 25 (01) ◽  
pp. 1660006 ◽  
Author(s):  
Alexandre Bonhomme ◽  
Philippe Mathieu ◽  
Sébastien Picault
Keyword(s):  
Decision Support ◽  
Road Traffic ◽  
Real Data ◽  
Multi Agent Systems ◽  
Agent Based ◽  
Traffic Conditions ◽  
Prototype Tool ◽  
Microscopic Models ◽  
Wide Range ◽  
Multi Agent

Among real-system applications of AI, the field of traffic simulation makes use of a wide range of techniques and algorithms. Especially, microscopic models of road traffic have been expanding for several years. Indeed, Multi-Agent Systems provide the capability of modeling the very diversity of individual behaviors. Several professional tools provide comprehensive sets of ready-made, accurate behaviors for several kinds of vehicles. The price in such tools is the difficulty to modify the nature of programmed behaviors, and the specialization in a single purpose, e.g. either studying resulting ows, or providing an immersive virtual reality environment. Thus, we advocate for a more exible approach for the design of multi-purpose tools for decision support. Especially, the use of geographical open databases offers the opportunity to design agent-based traffic simulators which can be continuously informed of changes in traffic conditions. Our proposal also makes decision support systems able to integrate environmental and behavioral modifications in a linear fashion, and to compare various scenarios built from different hypotheses in terms of actors, behaviors, environment and ows. We also describe here the prototype tool that has been implemented according to our design principles.

scholarly journals Spatiotemporal Modeling of the Smart City Residents’ Activity with Multi-Agent Systems

2019 ◽  
Vol 9 (10) ◽  
pp. 2059 ◽  
Author(s):  
Robert Olszewski ◽  
Piotr Pałka ◽  
Agnieszka Turek ◽  
Bogna Kietlińska ◽  
Tadeusz Płatkowski ◽  
...  
Keyword(s):  
Smart City ◽  
Social Activity ◽  
Real Data ◽  
Actor Network Theory ◽  
Spatial Arrangement ◽  
Multi Agent Systems ◽  
Agent Based ◽  
Agent Systems ◽  
Spatial Objects ◽  
Multi Agent

The article proposes the concept of modeling that uses multi-agent systems of mutual interactions between city residents as well as interactions between residents and spatial objects. Adopting this perspective means treating residents, as well as buildings or other spatial objects, as distinct agents that exchange multifaceted packages of information in a dynamic and non-linear way. The exchanged information may be reinforced or diminished during the process, which may result in changing the social activity of the residents. Utilizing Latour’s actor–network theory, the authors developed a model for studying the relationship between demographic and social factors, and the diversified spatial arrangement and the structure of a city. This concept was used to model the level of residents’ trust spatiotemporally and, indirectly, to study the level of social (geo)participation in a smart city. The devised system, whose test implementation as an agent-based system was done in the GAMA: agent-based, spatially explicit, modeling and simulation platform, was tested on both model and real data. The results obtained for the model city and the capital of Poland, Warsaw, indicate the significant and interdisciplinary analytical and scientific potential of the authorial methodology in the domain of geospatial science, geospatial data models with multi-agent systems, spatial planning, and applied social sciences.

An agent-based supplier selection framework

2015 ◽  
Vol 8 (2/3) ◽  
pp. 180-205 ◽  
Author(s):  
Alireza Jahani ◽  
Masrah Azrifah Azmi Murad ◽  
Md. Nasir bin Sulaiman ◽  
Mohd. Hasan Selamat
Keyword(s):  
Supply Chain ◽  
Supplier Selection ◽  
Information Overload ◽  
Case Based Reasoning ◽  
Multi Agent Systems ◽  
Content Type ◽  
Agent Based ◽  
Common Framework ◽  
Multi Agent ◽  
Case Based

Purpose – The purpose of this paper is to propose an approach that integrates three complementary perspectives, multi-agent systems, fuzzy logic and case-based reasoning. Unsatisfied customers, information overload and high uncertainty are the main challenges that are faced by today’s supply chains. In addition, a few existing agent-based approaches are tied to real-world supply chain functions like supplier selection. These approaches are static and do not adequately take the qualitative and quantitative factors into consideration. Therefore, an agent-based framework is needed to address these issues. Design/methodology/approach – The proposed approach integrates three complementary perspectives, multi-agent systems, fuzzy logic and case-based reasoning, as a common framework. These perspectives were rarely used together as a common framework in previous studies. Furthermore, an exploratory case study in an office furniture company is undertaken to illustrate the value of the framework. Findings – The proposed agent-based framework evaluates supply offers based on customers’ preferences, recommends alternative products in the case of stock-out and provides a collaborative environment among agents who represent different supply chain entities. The proposed fuzzy case-based reasoning (F-CBR) approach reduces the information overload by organizing them into the relevant cases that causes less overall search between cases. In addition, its fuzzy aspect addresses the high uncertainty of supply chains, especially when there are different customers’ orders with different preferences. Research limitations/implications – The present study does not include the functions of inventory management and negotiation between agents. Furthermore, only the case description and case retrieval phases of the case-based reasoning approach are investigated, and the remaining phases like case retaining, case reusing and case revising are not included in the scope of this paper. Originality/value – This framework balances the interests of different supply chain structural elements where each of them is represented by a specific agent for better collaboration, decision-making and problem-solving in a multi-agent environment. In addition, the supplier selection and order gathering mechanisms are developed based on customers’ orders.

Virtual Simulation of Road Traffic Based on Multi-agent Systems

2020 ◽  
pp. 188-217
Author(s):  
Hector Rafael Orozco Aguirre ◽  
Maricela Quintana Lopez ◽  
Saul Lazcano Salas ◽  
Victor Manuel Landassuri Moreno
Keyword(s):  
Road Traffic ◽  
Virtual Simulation ◽  
Multi Agent Systems ◽  
Agent Systems ◽  
Multi Agent

scholarly journals Multi-Agent Systems Applications in Energy Optimization Problems: A State-of-the-Art Review

Energies ◽  
2018 ◽  
Vol 11 (8) ◽  
pp. 1928 ◽  
Author(s):  
Alfonso González-Briones ◽  
Fernando De La Prieta ◽  
Mohd Mohamad ◽  
Sigeru Omatu ◽  
Juan Corchado
Keyword(s):  
Optimization Problems ◽  
State Of The Art ◽  
Smart Cities ◽  
Energy Optimization ◽  
Sensor Data ◽  
Multi Agent Systems ◽  
Agent Systems ◽  
Research Perspectives ◽  
Wide Range ◽  
Multi Agent

This article reviews the state-of-the-art developments in Multi-Agent Systems (MASs) and their application to energy optimization problems. This methodology and related tools have contributed to changes in various paradigms used in energy optimization. Behavior and interactions between agents are key elements that must be understood in order to model energy optimization solutions that are robust, scalable and context-aware. The concept of MAS is introduced in this paper and it is compared with traditional approaches in the development of energy optimization solutions. The different types of agent-based architectures are described, the role played by the environment is analysed and we look at how MAS recognizes the characteristics of the environment to adapt to it. Moreover, it is discussed how MAS can be used as tools that simulate the results of different actions aimed at reducing energy consumption. Then, we look at MAS as a tool that makes it easy to model and simulate certain behaviors. This modeling and simulation is easily extrapolated to the energy field, and can even evolve further within this field by using the Internet of Things (IoT) paradigm. Therefore, we can argue that MAS is a widespread approach in the field of energy optimization and that it is commonly used due to its capacity for the communication, coordination, cooperation of agents and the robustness that this methodology gives in assigning different tasks to agents. Finally, this article considers how MASs can be used for various purposes, from capturing sensor data to decision-making. We propose some research perspectives on the development of electrical optimization solutions through their development using MASs. In conclusion, we argue that researchers in the field of energy optimization should use multi-agent systems at those junctures where it is necessary to model energy efficiency solutions that involve a wide range of factors, as well as context independence that they can achieve through the addition of new agents or agent organizations, enabling the development of energy-efficient solutions for smart cities and intelligent buildings.

scholarly journals Use of the Multi-Agent Paradigm in Sustainable Tourism

2018 ◽  
Vol 7 (1) ◽  
pp. 5-24 ◽  
Author(s):  
Martina Husáková
Keyword(s):  
Complex Systems ◽  
Sustainable Tourism ◽  
Multi Agent Systems ◽  
Economic Prosperity ◽  
Cultural Economic ◽  
Bottom Up ◽  
Agent Based ◽  
Agent Systems ◽  
Multi Agent ◽  
In Silico Models

Abstract Complex systems are characterised by a huge amount of components, which are highly linked with each other. Tourism is one of the examples of complex systems collecting various activities leading to the enrichment of travellers in the view of receiving new experiences and increasing economic prosperity of specific destinations. The complex systems can be investigated with various bottom-up and top-down approaches. The multi-agent-based modelling is the bottom-up approach that is focused on the representation of individual entities for the exploration of possible interactions among them and their effects on surrounding environments. These systems are able to integrate knowledge of socio-cultural, economic, physical, biological or environmental systems for in-silico models development, which can be used for experimentation with a system. The main aim of the presented text is to introduce links between tourism, complexity and to advocate usefulness of the multi-agent-based systems for the exploration of tourism and its sustainability. The evaluation of suitability of the multi-agent systems in tourism is based on the investigation of fundamental characteristics of these two systems and on the review of specific applications of the multi-agent systems in sustainable tourism.

scholarly journals AGENT-BASED CROWD SIMULATION CONSIDERING EMOTION CONTAGION FOR EMERGENCY EVACUATION PROBLEM

2015 ◽  
Vol XL-1-W5 ◽  
pp. 193-196 ◽  
Author(s):  
H. Faroqi ◽  
M.-S. Mesgari
Keyword(s):  
Emergency Situation ◽  
Emergency Evacuation ◽  
Multi Agent Systems ◽  
Agent Based ◽  
Emergency Evacuations ◽  
R Language ◽  
Simulated Model ◽  
Agent Simulation ◽  
Adults And Children ◽  
Multi Agent

During emergencies, emotions greatly affect human behaviour. For more realistic multi-agent systems in simulations of emergency evacuations, it is important to incorporate emotions and their effects on the agents. In few words, emotional contagion is a process in which a person or group influences the emotions or behavior of another person or group through the conscious or unconscious induction of emotion states and behavioral attitudes. In this study, we simulate an emergency situation in an open square area with three exits considering Adults and Children agents with different behavior. Also, Security agents are considered in order to guide Adults and Children for finding the exits and be calm. Six levels of emotion levels are considered for each agent in different scenarios and situations. The agent-based simulated model initialize with the random scattering of agent populations and then when an alarm occurs, each agent react to the situation based on its and neighbors current circumstances. The main goal of each agent is firstly to find the exit, and then help other agents to find their ways. Numbers of exited agents along with their emotion levels and damaged agents are compared in different scenarios with different initialization in order to evaluate the achieved results of the simulated model. NetLogo 5.2 is used as the multi-agent simulation framework with R language as the developing language.

scholarly journals Trust in multi-agent systems

2004 ◽  
Vol 19 (1) ◽  
pp. 1-25 ◽  
Author(s):  
SARVAPALI D. RAMCHURN ◽  
DONG HUYNH ◽  
NICHOLAS R. JENNINGS
Keyword(s):  
Large Scale ◽  
State Of The Art ◽  
Comprehensive Treatment ◽  
Multi Agent Systems ◽  
Agent Based ◽  
Agent Systems ◽  
The Core ◽  
Open Distributed Systems ◽  
Multi Agent

Trust is a fundamental concern in large-scale open distributed systems. It lies at the core of all interactions between the entities that have to operate in such uncertain and constantly changing environments. Given this complexity, these components, and the ensuing system, are increasingly being conceptualised, designed, and built using agent-based techniques and, to this end, this paper examines the specific role of trust in multi-agent systems. In particular, we survey the state of the art and provide an account of the main directions along which research efforts are being focused. In so doing, we critically evaluate the relative strengths and weaknesses of the main models that have been proposed and show how, fundamentally, they all seek to minimise the uncertainty in interactions. Finally, we outline the areas that require further research in order to develop a comprehensive treatment of trust in complex computational settings.

A Clustering Approach Based on Cooperative Agents to Improve Decision Support in ERP

2019 ◽  
pp. 1-18
Author(s):  
Nadjib Mesbahi ◽  
Okba Kazar ◽  
Saber Benharzallah ◽  
Merouane Zoubeidi ◽  
Djamil Rezki
Keyword(s):  
Decision Support ◽  
Intelligent Systems ◽  
Multi Agent System ◽  
Multi Agent Systems ◽  
Agent System ◽  
Cooperative Agents ◽  
Distributed Problem Solving ◽  
Multi Agent ◽  
Complete Set ◽  
Clustering Approach

Multi-agent systems (MAS) are a powerful technology for the design and implementation of autonomous intelligent systems that can handle distributed problem solving in a complex environment. This technology has played an important role in the development of data mining systems in the last decade, the purpose of which is to promote the extraction of information and knowledge from a large database and to make these systems more scalable. In this chapter, the authors present a clustering system based on cooperative agents through a centralized and common ERP database to improve decision support in ERP systems. To achieve this, they use multi-agent system paradigm to distribute the complexity of k-means algorithm in several autonomous entities called agents, whose goal is to group records or observations on similar objects classes. This will help business decision makers to make good decisions and provide a very good response time by the use of the multi-agent system. To implement the proposed architecture, it is more convenient to use the JADE platform while providing a complete set of services and have agents comply with the specifications FIPA.

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