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FACTS & FIGURES

JCR Impact Factor: 0.699
JCR 5-Year IF: 0.674
Issues per year: 4
Current issue: May 2018
Next issue: Aug 2018
Avg review time: 107 days


PUBLISHER

Stefan cel Mare
University of Suceava
Faculty of Electrical Engineering and
Computer Science
13, Universitatii Street
Suceava - 720229
ROMANIA

Print ISSN: 1582-7445
Online ISSN: 1844-7600
WorldCat: 643243560
doi: 10.4316/AECE


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LATEST NEWS

2018-Jun-27
Clarivate Analytics published the InCites Journal Citations Report for 2017. The JCR Impact Factor of Advances in Electrical and Computer Engineering is 0.699, and the JCR 5-Year Impact Factor is 0.674.

2017-Jun-14
Thomson Reuters published the Journal Citations Report for 2016. The JCR Impact Factor of Advances in Electrical and Computer Engineering is 0.595, and the JCR 5-Year Impact Factor is 0.661.

2017-Feb-16
With new technologies, such as mobile communications, internet of things, and wide applications of social media, organizations generate a huge volume of data, much faster than several years ago. Big data, characterized by high volume, diversity and velocity, increasingly drives decision making and is changing the landscape of business intelligence, from governments to private organizations, from communities to individuals. Big data analytics that discover insights from evidences has a high demand for computing efficiency, knowledge discovery, problem solving, and event prediction. We dedicate a special section of Issue 4/2017 to Big Data. Prospective authors are asked to make the submissions for this section no later than the 31st of May 2017, placing "BigData - " before the paper title in OpenConf.

Read More »


    
 

  1/2010 - 14

Designing of Rescue Multi Agent System Based on Soft Computing Techniques

SHAMSHIRBAND, S. S. See more information about SHAMSHIRBAND, S. S. on SCOPUS See more information about SHAMSHIRBAND, S. S. on IEEExplore See more information about SHAMSHIRBAND, S. S. on Web of Science, SHIRGAHI, H. See more information about  SHIRGAHI, H. on SCOPUS See more information about  SHIRGAHI, H. on SCOPUS See more information about SHIRGAHI, H. on Web of Science, SETAYESHI, S. See more information about SETAYESHI, S. on SCOPUS See more information about SETAYESHI, S. on SCOPUS See more information about SETAYESHI, S. on Web of Science
 
Click to see author's profile in See more information about the author on SCOPUS SCOPUS, See more information about the author on IEEE Xplore IEEE Xplore, See more information about the author on Web of Science Web of Science

Download PDF pdficon (625 KB) | Citation | Downloads: 1,038 | Views: 4,778

Author keywords
multi agent system, reinforcement learning, cooperative, rescue agents

References keywords
learning(7), agent(6), multi(5)
Blue keywords are present in both the references section and the paper title.

About this article
Date of Publication: 2010-02-27
Volume 10, Issue 1, Year 2010, On page(s): 79 - 83
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2010.01014
Web of Science Accession Number: 000275458900014
SCOPUS ID: 77954686893

Abstract
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The goal of rescuer Multi agent's project is to simulate urban unpleasant incidents and events to reduce the rate of detriment of this event. The various rescuer forces attempt to do their best duties. One of the most important problems in multi agent system is communication among agents. Most of the various algorithms in multi agent system so far has share of duties, negotiation, learning and searching need to various forms of communication among agents. In the paper we attempt to rescue the most wounded using Reinforcement learning to be able to gain the shortest time.


References | Cited By  «-- Click to see who has cited this paper

[1] M. Dorigo, V. Maniezzo, and A. Colorni, "Ant System: Optimization by a colony of cooperating agents", IEEE Transactions on Systems, Man, and Cybernetics, pp. 29-41, 1996
[CrossRef] [Web of Science Times Cited 4857] [SCOPUS Times Cited 6782]


[2] H. Kawamura, M. Yamamoto, K. Suzuki, A Ohuchiand, "Multiple Ant Colonies Algorithm Based on Colony Level Interactions", IEICE Trans. Fundamentals, vol. E83-A, no. 2, pp. 371-379, February 2000

[3] E. Bonabeau, and G. Theraulaz, "Swarm Smarts", Scientific American, pp. 72-79, March 2000
[CrossRef] [Web of Science Times Cited 81] [SCOPUS Times Cited 134]


[4] S. Amirpour-Amraii, B. Behsaz, M. Izadi, H. Janzadeh, F. Molazem, A. Rahimi, M. Tavakoli-Ghinani, and H. Vosoughpour, "S.O.S. an attempt towards a multi-agent rescue team", Amirkabir University of Technology Press, Tehran, Iran, pp. 1-12, 2004

[5] M. Hoshino, H. Asama, K. Kawabata, Y. Kunii, and I. Endo, "Communication learning for cooperation among autonomous robots", 26th Annual Conference of the IEEE, vol. 3, pp. 2111-2116, 2000
[CrossRef] [SCOPUS Times Cited 2]


[6] T. R. Payne, M. Paolucci, R. Singh, and K. Sycara, "Communicating agents in open multi agent systems", Carnegie Mellon University press, The Robotic Institute, Pittsburg, USA, pp. 1-10, 2002

[7] J. Ferber, "Reactive Distributed Artificial Intelligence: Principles and Applications", Foundations of Distributed Artificial Intelligence, John Wiley Sixth-Generation Computer Technology Series, John Wiley & Sons, Inc. New York, NY, USA, pp. 287-314, 1996

[8] P. Y. Glorennec, "Reinforcement Learning: an Overview," ESIT, Aachen, Germany, pp. 1-19, September 2000

[9] R. S. Sutton and A. G. Barto, Sutton, "Reinforcement Learning: An Introduction", The MIT Press, Cambridge, MA, 1998 [PermaLink]

[10] D. L. Grecu, and D. C. Brown, "Dimensions of Leaning in Agent-Based Design", 4th International Conference on AI in Design, Stanford, CA, pp. 1-6, 1996

[11] K. Shibata and K. Ito, "Autonomous Learning of Reward Distribution for Each Agent in Multi-Agent Reinforcement Learning", Department of Electrical & Electronic Engineering, Oita University Press, Japan, pp. 1-8, 2000

[12] E. Alonso, M. Dinverto, D. Kudenko, M. Luck, and J. Noble, "Learning in multi agent systems", The Knowledge Engineering Review, vol.16, no. 3, pp. 277-284, September 2001
[CrossRef] [Web of Science Times Cited 51] [SCOPUS Times Cited 68]


[13] F. Fernandez, and L. E. Parker, "Learning in large cooperative multi robot domains", Center for engineering science advanced research computer science and mathematics division Oak Ridge national laboratory, USA, pp. 1-29, 2001

References Weight

Web of Science® Citations for all references: 4,989 TCR
SCOPUS® Citations for all references: 6,986 TCR

Web of Science® Average Citations per reference: 384 ACR
SCOPUS® Average Citations per reference: 537 ACR

TCR = Total Citations for References / ACR = Average Citations per Reference

We introduced in 2010 - for the first time in scientific publishing, the term "References Weight", as a quantitative indication of the quality ... Read more

Citations for references updated on 2018-07-13 08:46 in 33 seconds.




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Faculty of Electrical Engineering and Computer Science
Stefan cel Mare University of Suceava, Romania


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