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Adapt-Traf: An adaptive multiagent road traffic management system based on hybrid ant-hierarchical fuzzy model

Habib M. Kammoun, Ilhem Kallel, Jorge Casillas, Ajith Abraham, Adel M. Alimi
2014 Transportation Research Part C: Emerging Technologies  
This paper proposes an adaptive multiagent system based on the ant colony behavior and the hierarchical fuzzy model.  ...  The proposed system is implemented and simulated under a multiagent platform in order to discuss the improvement of the global road traffic quality in terms of time, fluidity and adaptivity.  ...  Acknowledgments This work was supported, in part, by the General Direction of Scientific Research (DGRST) in Tunisia (ARUB program) and by the Spanish Ministry of Science and Innovation (grant no.  ... 
doi:10.1016/j.trc.2014.03.003 fatcat:sahnsazdlvevvoplvgofad4hvy

Bio-inspired multi-agent systems for reconfigurable manufacturing systems

Paulo Leitão, José Barbosa, Damien Trentesaux
2012 Engineering applications of artificial intelligence  
The Multi-Agent System (MAS) paradigm offers an alternative way to design this kind of system based on decentralized control using distributed, autonomous agents, thus replacing the traditional centralized  ...  An industrial automation case study is used to illustrate a bio-inspired method based on potential fields to dynamically route pallets.  ...  Acknowledgments The experimental work was performed by a project team, including Nadine Zbib, Cyrille Pach, Yves Sallez, Thierry Berger, with the help and support of the AIP-PRIMECA team.  ... 
doi:10.1016/j.engappai.2011.09.025 fatcat:ldfomxk5r5fm7mkzhj6efpchsa

A Review of Platforms for the Development of Agent Systems [article]

Constantin-Valentin Pal, Florin Leon, Marcin Paprzycki, Maria Ganzha
2020 arXiv   pre-print
It aims to serve as a reference point for people interested in developing agent systems.  ...  Agent-based computing is an active field of research with the goal of building autonomous software of hardware entities.  ...  SLAPP is a simulation shell for agent systems based on a swarm-like agent protocol implemented in Python 3.  ... 
arXiv:2007.08961v1 fatcat:3ddtajdqv5fftldoqobr2y6y4u

2019 Index IEEE Transactions on Systems, Man, and Cybernetics: Systems Vol. 49

2019 IEEE Transactions on Systems, Man & Cybernetics. Systems  
Inceoglu, A., +, TSMC Jan. 2019 192-205 Enhancing Binocular Depth Estimation Based on Proactive Perception and Action Cyclic Learning for an Autonomous Developmental Robot.  ...  ., +, TSMC June 2019 1270-1284 Energy Internet Guest Editorial Special Issue on New Trends in Energy Internet: Artificial Intelligence-Based Control, Network Security, and Management.  ...  Open loop systems  ... 
doi:10.1109/tsmc.2019.2956665 fatcat:xhplbanlyne7nl7gp2pbrd62oi

MAGENTA technology case studies of magenta i-scheduler for road transportation

Petr Skobelev, Andrey Glaschenko, Ilya Grachev, Sergey Inozemtsev
2007 Proceedings of the 6th international joint conference on Autonomous agents and multiagent systems - AAMAS '07  
The paper describes functionality of Magenta Multi-Agent Logistics i-Scheduler Engine presented on AAMAS 2006 conferences and gives examples of its application in business domain.  ...  This results in a unique ability to combine inbound and outbound deliveries, different fleets or private networks, driving more value from finding effective backhauls and consolidations.  ...  more traditional approaches rather than on exploring new features and advantages of multi-agent systems based on swarm intelligence principles [12] .  ... 
doi:10.1145/1329125.1329455 dblp:conf/atal/SkobelevGGI07 fatcat:g3qhdwcdnnejdfqfofw2qxsqgi

Swarm intelligence systems for transportation engineering: Principles and applications

Dušan Teodorović
2008 Transportation Research Part C: Emerging Technologies  
Swarm intelligence (Beni and Wang, 1989) is the branch of Artificial Intelligence based on study of behavior of individuals in various decentralized systems.  ...  Swarm intelligence is the branch of artificial intelligence based on study of behavior of individuals in various decentralized systems.  ...  Acknowledgments The author would like to thank the anonymous referees whose comments and suggestions have significantly improved this article.  ... 
doi:10.1016/j.trc.2008.03.002 fatcat:lbif2caiqbhk5l3stfxk5yd2iu

Stabilization Methods for a Multiagent System with Complex Behaviours

Florin Leon
2015 Computational Intelligence and Neuroscience  
The main focus of the paper is the stability analysis of a class of multiagent systems based on an interaction protocol which can generate different types of overall behaviours, from asymptotically stable  ...  We present several interpretations of stability and suggest two methods to assess the stability of the system, based on the internal models of the agents and on the external, observed behaviour.  ...  Conditions for swarm stability of nonlinear high-order multiagent systems were also described based on the idea of space transformation, showing that swarm stability can be ensured by sufficient connectivity  ... 
doi:10.1155/2015/236285 pmid:26097491 pmcid:PMC4444567 fatcat:776mew25mjf6vfm4yxcadrisfe

Multiple Mobile Robot Systems [chapter]

Lynne E. Parker, Daniela Rus, Gaurav S. Sukhatme
2016 Springer Handbook of Robotics  
Temporal changes in system-level swarm behavior are addressed by Hoff et al. [53.150] who show how a swarm can change and improve its foraging behavior by switching between algorithms based on the environment  ...  This work computes the expected error characteristics for an ideal algorithm, and compares this to the actual error in an algorithm based on multilateration, drawing the important conclusion that the error  ... 
doi:10.1007/978-3-319-32552-1_53 fatcat:rijl5w2zuvfyhjyx3drntjwvam

Towards efficient multiagent task allocation in the RoboCup Rescue: a biologically-inspired approach

Fernando dos Santos, Ana L. C. Bazzan
2010 Autonomous Agents and Multi-Agent Systems  
We use a swarm intelligence based approach, address all characteristics, and compare it to other two GAP-based algorithms.  ...  This paper addresses team formation in the RoboCup Rescue centered on task allocation.  ...  Acknowledgments This research is partially supported by the Air Force Office of Scientific Research (AFOSR) (grant number FA9550-06-1-0517) and by the Brazilian National Council for Scientific and Technological  ... 
doi:10.1007/s10458-010-9136-3 fatcat:ncrbocwoabdbrbdekwpjce7aam

Special Issue on Deep Reinforcement Learning for Emerging IoT Systems

Jia Hu, Peng Liu, Hong Liu, Obinna Anya, Yan Zhang
2020 IEEE Internet of Things Journal  
Jia Hu received the B.Eng. and M.Eng. degrees in electronic engineering from the Huazhong  ...  Peng Liu received the B.S. and M.S. degrees in computer science and technology from Hangzhou Dianzi University, Hangzhou, China, in 2001 and 2004, respectively, and  ...  To solve the problem of inadequately labeled sample data, an intelligent auto-labeling scheme based on DQN is developed.  ... 
doi:10.1109/jiot.2020.2998256 fatcat:rct75tsesbh7lkjmhuyogfi4ym

Multipotent Systems: Combining Planning, Self-Organization, and Reconfiguration in Modular Robot Ensembles

Oliver Kosak, Constantin Wanninger, Alwin Hoffmann, Hella Ponsar, Wolfgang Reif
2018 Sensors  
Mobile multirobot systems play an increasing role in many disciplines.  ...  Because typically a high degree of autonomy in such systems is a prerequisite for their practical usage, we also present the integration of necessary mechanisms and algorithms for achieving the systems  ...  Those range from complex planning and coordination approaches to determine useful action sequences [21] , over so-called swarm intelligence technologies [22, 23] exploiting local interactions between  ... 
doi:10.3390/s19010017 fatcat:oq3ohsfduzbxtcjx2m42jv4sfq

An agent-based hyper-heuristic approach to combinatorial optimization problems

Richard Malek
2010 2010 IEEE International Conference on Intelligent Computing and Intelligent Systems  
This paper introduces a framework based on multi-agent system for solving problems of combinatorial optimization. The framework allows running various meta-heuristic algorithms simultaneously.  ...  Our hyper-heuristic approach is defined as a high-level search in algorithm space implemented within agents.  ...  In both cases we have to select a feasible subset of all available algorithms and in case of sequencing even a proper algorithm order.  ... 
doi:10.1109/icicisys.2010.5658624 fatcat:6mp5pqd6x5dpvenoasrq2om4su

Current advancements on autonomous mission planning and management systems: An AUV and UAV perspective

Adham Atyabi, Somaiyeh MahmoudZadeh, Samia Nefti-Meziani
2018 Annual Reviews in Control  
This paper serves as an introduction to UVs mission planning and management systems aiming to highlight some of the recent developments in the field of autonomous underwater and aerial vehicles in addition  ...  onboard intelligence.  ...  An autonomous system, on the other hand, can select amongst multiple possible action sequences in order to achieve its goals.  ... 
doi:10.1016/j.arcontrol.2018.07.002 fatcat:fq5q25mqgjhczjtojlganzrmue

Coordinated Control of Distributed Traffic Signal Based on Multiagent Cooperative Game

Zhenghua Zhang, Jin Qian, Chongxin Fang, Guoshu Liu, Quan Su, Zhipeng Cai
2021 Wireless Communications and Mobile Computing  
This paper proposes multiagent reinforcement learning based on cooperative game (CG-MARL) to design the intersection as an agent structure.  ...  The distributed multiagent RL (MARL) can avoid this kind of problem by observing some areas of each local RL in the complex plane traffic area.  ...  In recent years, the algorithm of traffic signal control is developing towards intelligence, for example, swarm intelligence algorithms (particle swarm optimization (PSO), ant colony optimization (ACO)  ... 
doi:10.1155/2021/6693636 fatcat:7amnnzidtjbhnlnydlzfiiydg4

A Multiagent Approach for Metaheuristics Hybridization Applied to the Traveling Salesman Problem

Givanaldo R. Souza, Elizabeth F.G. Goldbarg, Marco C. Goldbarg, Anne M.P. Canuto
2012 2012 Brazilian Symposium on Neural Networks  
This paper proposes a multiagent approach for metaheuristics hybridization inspired on the popular technique called Particle Swarm Optimization (PSO).  ...  Each particle is an autonomous agent with memory and methods for learning and making decisions. The proposed approach is applied to the Traveling Salesman Problem in order to test its effectiveness.  ...  INTRODUCTION Swarm intelligence is an artificial intelligence subarea related to the design of intelligent systems based on the behavior of social insects such as ants and bees, as well as on other animal  ... 
doi:10.1109/sbrn.2012.39 dblp:conf/sbrn/SouzaGGC12 fatcat:szpkdgkeq5axng2izz6setuzwm
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