Location via proxy:   [ UP ]  
[Report a bug]   [Manage cookies]                
skip to main content
10.5555/3400397.3400501acmconferencesArticle/Chapter ViewAbstractPublication PageswscConference Proceedingsconference-collections
research-article

The intersection of agent based models and fuzzy cognitive maps: a review of an emerging hybrid modeling practice

Published: 18 May 2020 Publication History

Abstract

Agent Based Modeling (ABMs) and Fuzzy Cognitive Mapping (FCM) are complementary modeling techniques: the former represents interacting agents across a landscape over time but does not specify how to encapsulate subjective behaviors in agents, whereas the latter can model a subjective behavior but lacks the ability to scale it to a population or do it over time. These techniques are increasingly used together, particularly as hybrid models. We propose the first review of this emerging practice and identified 31 articles that combined the two techniques. Our analysis revealed three different high-level architectures to structure the combined use of ABMs and FCMs, such as using an interface or embedding an FCM into each agent. Our review provides a snapshot of an emerging field, thus assembling the evidence-base to identify potential areas for future work, such as consolidating and standardizing software development efforts in a currently fragmented field.

References

[1]
Aizstrauts, A., E. Ginters, I. Lauberte, and M. A. P. Eroles. 2013. "Multi-level Architecture on Web Services Based Policy Domain Use Cases Simulator." in Workshop on Enterprise and Organizational Modeling and Simulation, edited by J. Barjis, A. Gupta, and A. Meshkat, 130--145. Berlin, Heidelberg, Springer
[2]
Alibage, A, Jetter, A., Aminpour, P., Gray, S., and S. Scyphers. 2018. "Exploratory Participatory Modelling with FCM to Overcome Uncertainty: Improving Safety Culture in Oil and Gas Operations." In 9th International Congress on Environmental Modelling and Software, June 24-28, Fort Collins, Colorado, USA
[3]
Alizadeh, Y., and A. Jetter. 2017. "Content Analysis Using Fuzzy Cognitive Map (FCM): A Guide to Capturing Causal Relationships from Secondary Sources of Data." In Portland International Conference on Management of Engineering and Technology (PICMET, July 23-29, Portland, OR, 1--11.
[4]
Bahri, O. 2018. Precision Agriculture: Modeling and Simulation. Thesis, School of Science and Engineering, Al Akhawayn University, Ifran, Morocco. http://www.aui.ma/sse-capstone-repository/pdf/spring-2018/PRECISION%20AGRICULTURE-%20MODELING%20AND%20SIMULATION.pdf, accessed 16th August
[5]
Balaban, M. A. 2014. "Toward a theory of multi-method modeling and simulation approach". Proceedings of the Winter Simulation Conference 2014, December 7th-10th, Savanah, GA, USA
[6]
Beroule, B., A. J. Fougères, & E. Ostrosi. 2015. "Agent-Based Product Configuration: Towards Generalized Consensus Seeking." International Journal of Computer Science Issues (IJCSI), 11(6): 1
[7]
Beroule, B., A. J. Fougeres, & E. Ostrosi. 2014. "Engineering change management through consensus seeking by fuzzy agents." 2014 Second World Conference on Complex Systems (WCCS), Nov 10th-13th, Agadir, Morroco, 542--547.
[8]
Bhagwat, P. C., A. Marcheselli, J. C. Richstein, E. J. Chappin, and L. J. De Vries. 2017. "An analysis of a forward capacity market with long-term contracts". Energy policy: 111(C), 255--267.
[9]
Bien, Z. Z., and H. E. Lee. 2007. "Effective learning system techniques for human-robot interaction in service environment.". Knowledge-Based Systems: 20(5), 439--456.
[10]
Borrie, D., and C.S. Özveren. 2007 "Realisation of Fuzzy Cognitive Agents in the Electrical Trading". 2007 42nd International Universities Power Engineering Conference, September 4th-6th, Brighton, UK, 1159--1163.
[11]
Borrie, D., S. Isnandar, and C. S. Özveren. 2006a. "Simulation of Complex Environments: The Fuzzy Cognitive Agent." In Proceedings of the Sixth International Conference on Intelligent Systems Design and Applications (ISDA'06), October 16th-18th, 348--353
[12]
Borrie, D., S. Isnandar, and C. S. Ozveren. 2006b. "The Use of Fuzzy Cognitive Agents to Simulate Trading Patterns." Proceedings of the 41st International Universities Power Engineering Conference, September 6th-8th, 1077--1081.
[13]
Borshchev, A. 2013. The big book of simulation modeling: multimethod modeling with AnyLogic 6. Chicago: AnyLogic North America.
[14]
Chahal, K. 2010. "A generic framework for hybrid simulation in healthcare." Doctoral dissertation, Brunel University School of Information Systems, Computing and Mathamatics.
[15]
Conte, R., B. Edmonds, S. Moss, and R. K. Sawyer. 2001. "Sociology and social theory in agent based social simulation: A symposium". Computational & Mathematical Organization Theory, 7(3): 183--205.
[16]
Dejam, B. 2015. "Design and Simulation of RFID-Enabled Aircraft Reverse Logistics Network via Agent-Based Modeling". Doctoral dissertation, Concordia University Montreal, Quebec, Canada. Concordia University.
[17]
Eldabi, T., S. Brailsford, A. Djanatliev, M. Kunc, N. Mustafee, and A. F. Osorio. 2018. "Hybrid simulation challenges and opportunities: a life-cycle approach". Winter Simulation Conference, December 9th-12th, Gothenburg, Sweden, 1500--1514.
[18]
Elsawah, S., J. H. A. Guillaume, T. Filatovac, J. Rook, A. J. Jakeman. 2015. "A Methodology for Eliciting, Representing, and Analysing Stakeholder Knowledge for Decision Making on Complex Socio-Ecological Systems: From Cognitive Maps to Agent-Based Models". Journal of Environmental Management, 151(2015): 500--516.
[19]
Epstein, J. M., and R. Axtell. 1996. Growing artificial societies: social science from the bottom up. Brookings Institution Press.
[20]
Felix, G, G. Nápoles Ruiz, R. Falcon, W. Froelich, and K. Vanhoof. 2017. "A Review On Methods and Software for Fuzzy Cognitive Maps." Artificial intelligence review, (2017): 1--31
[21]
Fogel, D.B. 2006. Evolutionary Computation: Toward a New Philosophy of Machine Intelligence, Volume 1. Hoboken NJ: Wiley & Sons.
[22]
Fougères, A. J. 2013. "A Modelling Approach Based on Fuzzy Agents." International Journal of Computer Science Issues (IJCSI), 9(6): 19.
[23]
Fougères, A. J. 2016. "Towards Quantum Agents: The Superposition State Property." International Journal of Computer Science Issues, 13(5): 20.
[24]
Ghaderi, S. F., A. Azadeh, B. P. Nokhandan, and E. Fathi. 2012. "Behavioral Simulation and Optimization of Generation Companies in Electricity Earkets by Fuzzy Cognitive Map". Expert Systems with Applications, 39(5): 4635--4646.
[25]
Giabbanelli, P. J. 2014. "Computational Models of Chronic Diseases: Understanding and Leveraging Complexity". Doctoral dissertation, Science: Department of Biomedical Physiology and Kinesiology.
[26]
Giabbanelli, P. J., Fattoruso, M., and Norman, M.L. 2019. "CoFluences: Simulating the Spread of Social Influences via a Hybrid Agent-Based/Fuzzy Cognitive Maps Architecture". In Proceedings of the ACM SIGSIM Conference on Principles of Advanced Discrete Simulation. June 3rd-5th, Chicago, Illinois.
[27]
Giabbanelli, P. J., S. A. Gray, and P. Aminpour. 2017. "Combining Fuzzy Cognitive Maps with Agent-Based Modeling: Frameworks and Pitfalls of a Powerful Hybrid Modeling Approach to Understand Human-Environment Interactions". Environmental Modelling & Software, 95: 320--325.
[28]
Giabbanelli, P. J., A. A. Tawfik, and V. K. Gupta. 2019. "Learning Analytics to Support Teachers' Assessment of Problem Solving: A Novel Application for Machine Learning and Graph Algorithms". In Utilizing Learning Analytics to Support Study Success, 175--199
[29]
Gilbert, N. 2008. Agent-based models, Newbury Park, California. Sage.
[30]
Ginters, E., A. Aizstrauts, D. Aizstrauta, I. Lauberte, M. Angel, P. Eroles, R. Buil, P. Sonntagbauer and S. Sonntagbauer. 2013. "FP7 FUPOL Project-Innovation In Policy Science." CBU International Conference Proceedings. Central Bohemia University, 231.
[31]
Glykas, M. 2010. Fuzzy cognitive maps: Advances in Theory, Methodologies, Tools and Applications. Springer Science & Business Media.
[32]
Goldstein, J. 1999. "Emergence as a Construct: History and Issues." Emergence, 1(1): 49--72.
[33]
Gras, R., D. Devaurs, A. Wozniak, and A. Aspinall. 2009. "An Individual-Based Evolving Predator-Prey Ecosystem Simulation Using a Fuzzy Cognitive Map as the Behavior Model". Artificial life, 15(4): 423--463.
[34]
Gray, S., A. Voinov, M. Paolisso, R. Jordan, T. BenDor, P. Bommel, P. Glynn, B. Hedelin, K. Hubacek, J. Introne, and N. Kolagani. 2018. "Purpose, Processes, Partnerships, and Products: Four Ps to Advance Participatory Socio - Environmental Modeling". Ecological applications, 28(1): 46--61.
[35]
Jackson, P. J. 2013. "A Framework for Software Modelling in Social Science Research". Doctoral Dissertation, Simon Fraser University.
[36]
Jetter, A. J. 2006. "Fuzzy Cognitive Maps for Engineering and Technology Management: What Works in Practice?". In Proceedings of the 2006 Technology Management for the Global Future-PICMET 2006 Conference, July 8th-13th, Istanbul, Turkey, 498--512.
[37]
Jetter, A. J., and K. Kok. 2014 "Fuzzy Cognitive Maps for Futures Studies---A Methodological Assessment of Concepts and Methods." Futures. 61(2014): 45--57.
[38]
Jordan, R., S. Gray, M. Zellner, P. D. Glynn, A. Voinov, B. Hedelin, E. J. Sterling, K. Leong, L. S. Olabisi, K. Hubacek, and P. Bommel. 2018. "Twelve Questions for the Participatory Modeling Community". Earth's Future, 6(8): 1046--1057.
[39]
Karavas, C. S., G. Kyriakarakos, K. G. Arvanitis, and G. Papadakis. 2015. "A Multi-Agent Decentralized Energy Management System Based on Distributed Intelligence for the Design and Control of Autonomous Polygeneration Microgrids". Energy Conversion and Management. 100(103): 166--179.
[40]
Kazemifard, M., A. Zaeri, N. Ghasem-Aghaee, M. A. Nematbakhsh, and F. Mardukhi. 2011. "Fuzzy Emotional COCOMO II Software Cost Estimation (FECSCE) Using Multi-Agent Systems". Applied Soft Computing, 2(11): 2260--2270.
[41]
Kennedy, J., R. Eberhart. 1995. "Particle Swarm Optimiztion." Proceedings of IEEE International Conference on Neural Networks, 4: 1942--1948.
[42]
Khater, M., E. Salehi, and R. Gras. 2012 "The Emergence of New Genes in Ecosim and its Effect on Fitness". Simulated Evolution and Learning: 9th International Conference, SEAL 2012, December 16th-19th, Hanoi, Vietnam, 52--61.
[43]
Knight, C. J., D. J. Lloyd, and A. S. Penn, 2014. "Linear and Sigmoidal Fuzzy Cognitive Maps: An Analysis of Fixed Points". Applied Soft Computing 15(2014): 193--202.
[44]
Kosko, B. 1986 "Fuzzy Cognitive Maps." International Journal of Man-Machine Studies, 24(1): 65--75.
[45]
Kosuge, K., and Hirata, Y. 2004. "Human-Robot Interaction". IEEE International Conference on Robotics and Biomimetics, August 22nd-26th, Shenyang, China
[46]
Lavin, E. A., P. J. Giabbanelli, A. T. Stefanik, S. A. Gray, & R. Arlinghaus. 2018. "Should We Simulate Mental Models to Assess Whether they Agree?". Proceedings of the Annual Simulation Symposiun, April 15th-18th, Baltimore, Maryland, 6
[47]
Lee, K. C., N. Lee, and H. Lee. 2012a. "Multi-Agent Knowledge Integration Mechanism Using Particle Swarm Optimization". Technological Forecasting & Social Change, 79(3): 469--484.
[48]
Lee, K. C., H. Lee, and N. Lee. 2012b. "Agent Based Mobile Negotiation for Personalized Pricing of Last Minute Theatre Tickets". Expert Systems With Applications, 39(10): 9255--9263.
[49]
Lee, K. C., H. Lee, N. Lee, and J. Lim. 2013. "An Agent-Based Fuzzy Cognitive Map Approach to the Strategic Marketing Planning for Industrial Firms". Industrial Marketing Management, 42(4): 552--563.
[50]
Leong, P., and M. Chunyan. 2005. "Fuzzy Cognitive Agents in Shared Virtual Worlds". In Proceedings of the 2005 International Conference on Cyberworlds (CW'05), November 23rd-25th, Singapore, 368--372.
[51]
Mago, V. K., L. Bakker, E. I. Papageorgiou, A. Alimadad, P. Borwein, and V. Dabbaghian. 2012. "Fuzzy Cognitive Maps and Cellular Automata: An Evolutionary Approach for Social Systems Modelling". Applied Soft Computing. 12(12): 3771--3784.
[52]
Mendonça, M., I. R. Chrun, F. Neves Jr, & L. V. Arruda. 2017. "A Cooperative Architecture for Swarm Robotic Based on Dynamic Fuzzy Cognitive Maps". Engineering Applications of Artificial Intelligence, 100(59): 122--132.
[53]
Miao, C. Y., A. Goh, Y. Miao, and Z. H. Yang. 2002. "Agent that Models, Reasons and Makes Decisions." Knowledge-Based Systems, 3(15): 203--211.
[54]
Muhammad, A., A. Jetter, and T. Daim. 2011. "Development of Fuzzy Cognitive Map (FCM) - Based Scenarios for Wind Energy." International Journal of Energy Sector Management. 5(4): 564--584.
[55]
Murungweni, C., M. van Wijk, J. Andersson, E. Smaling, and K. Giller. 2011. "Application of Fuzzy Cognitive Mapping in Livelihood Vulnerability". Ecology and Society. 16(4): 8.
[56]
Mustafee, N., and J. H. Powell. 2018. "From Hybrid Simulation to Hybrid Systems Modelling". Proceedings of the 2018 Winter Simulation Conference, December 9th-12th, Gothenburg, Sweden, 1430--1439.
[57]
Nacházel, T. 2015. "Optimization of Decision-Making in Artificial Life". 2015 International Conference on Intelligent Environments, July 15th-17th, Prague, Czech Republic
[58]
Ortolani, L., N. McRoberts, N. Dendoncker, and M. Rounsevell. 2010. "Analysis of Farmers' Concepts of Environmental Management Measures: An Application of Cognitive Maps and Cluster Analysis in Pursuit of Modelling Agents' Behaviour". Fuzzy Cognitive Maps, 247: 363--381.
[59]
Ostrosi, E., and A. J. Fougères. 2018. "Intelligent Virtual Manufacturing Cell Formation in Cloud-Based Design and Manufacturing". Engineering Applications of Artificial Intelligence. 76: 80--95.
[60]
Ostrosi, E., A. J. Fougères, and M. Ferney. 2012. "Fuzzy Agents for Product Configuration in Collaborative and Distributed Design." Applied Soft Computing, 12(8): 2091--2105.
[61]
Papageorgiou, E. I., and J. L. Salmeron. 2013. "A Review of Fuzzy Cognitive Maps Research During the Last Decade". IEEE Transactions on Fuzzy Systems, 1(21): 66--79.
[62]
Papageorgiou, E. I. 2013. Fuzzy Cognitive Maps for Applied Sciences and Engineering: From Fundamentals to Extensions and Learning Algorithms, New York, Springer Science & Business Media.
[63]
Papageorgiou, E. I., M. F. Hatwágner, A. Buruzs, and L. T. Kóczy. 2017. "A Concept Reduction Approach for Fuzzy Cognitive Map Models in Decision Making and Management". Neurocomputing, 100(232): 16--33.
[64]
Pillutla, V.S., and Giabbanelli, P.J. 2019. "Iterative Generation of Insight From Text Collections Through Mutually Reinforcing Visualizations and Fuzzy Cognitive Maps". Applied Soft Computing 76 (2019): 459--472.
[65]
Raoufi, M., and F. A. Robinson. 2018. "Fuzzy Agent-Based Modeling of Construction Crew Motivation and Performance". Journal of Computing in Civil Engineering. 32(5): 04018035.
[66]
Ringler, P., D. Keles, and W. Fichtner. 2016. "Agent-Based Modelling and Simulation of Smart Electricity Grids and Markets--A Literature Review". Renewable and Sustainable Energy Reviews, 100(57): 205--215.
[67]
Sinha, J., and K. R. Kiran. 2016. "Intelligent Agent Architecture for Runtime Software Evolution". International Journal of Control Theory and Applications, 9(17): 8455--8462.
[68]
Swinerd, C., and McNaught, K. R. 2012. "Design classes for hybrid simulations involving agent-based and system dynamics models". Simulation Modelling Practice and Theory, (25): 118--133.
[69]
Voinov, A., K. Jenni, S. Gray, N. Kolagani, P. D. Glynn, P. Bommel, C. Prell, M. Zellner, M. Paolisso, R. Jordan, and E. Sterling. 2018. "Tools and Methods in Participatory Modeling: Selecting the Right Tool for the Job". Environmental Modelling & Software 109: 232--255.
[70]
Wildenberg, M., M. Bachhofer, M. Adamescu, G. De Blust, R. Diaz-Delgadod, K. G. Q. Isak, F. Skov, and V. Riku. 2010. "Linking Thoughts to Flows-Fuzzy Cognitive Mapping as a Tool for Integrated Landscape Modelling". In Proceedings of the 2010 International Conference on Integrative Landscape Modeling: Linking Environmental, Social and Computer Science, (3): 5
[71]
Wilensky, U. 1999. "Center for Connected Learning and Computer-Based Modeling". Netlogo, Northwestern University
[72]
Xiao, J., P. Andelfinger, D. Eckhoff, W. Cai, and A. Knoll. 2019. "A Survey on Agent-based Simulation Using Hardware Accelerators". ACM Computing Surveys. 51(6): 131.
[73]
Ye, P., S. Wang, and F. Y. Wang. 2018. "A General Cognitive Architecture for Agent-Based Modeling in Artificial Societies". IEEE Transactions on Computational Social Systems 5(1): 176--185.

Cited By

View all
  • (2021)How modeling methods for fuzzy cognitive mapping can benefit from psychology researchProceedings of the Winter Simulation Conference10.5555/3522802.3522971(1-12)Online publication date: 13-Dec-2021
  1. The intersection of agent based models and fuzzy cognitive maps: a review of an emerging hybrid modeling practice

      Recommendations

      Comments

      Information & Contributors

      Information

      Published In

      cover image ACM Conferences
      WSC '19: Proceedings of the Winter Simulation Conference
      December 2019
      3627 pages
      ISBN:9781728132839

      Sponsors

      Publisher

      IEEE Press

      Publication History

      Published: 18 May 2020

      Check for updates

      Qualifiers

      • Research-article

      Conference

      WSC '19
      Sponsor:
      WSC '19: Winter Simulation Conference
      December 8 - 12, 2019
      Maryland, National Harbor

      Acceptance Rates

      Overall Acceptance Rate 3,413 of 5,075 submissions, 67%

      Contributors

      Other Metrics

      Bibliometrics & Citations

      Bibliometrics

      Article Metrics

      • Downloads (Last 12 months)8
      • Downloads (Last 6 weeks)0
      Reflects downloads up to 03 Feb 2025

      Other Metrics

      Citations

      Cited By

      View all
      • (2021)How modeling methods for fuzzy cognitive mapping can benefit from psychology researchProceedings of the Winter Simulation Conference10.5555/3522802.3522971(1-12)Online publication date: 13-Dec-2021

      View Options

      Login options

      View options

      PDF

      View or Download as a PDF file.

      PDF

      eReader

      View online with eReader.

      eReader

      Figures

      Tables

      Media

      Share

      Share

      Share this Publication link

      Share on social media