Using Surrogate Models to Calibrate Agent-based Model Parameters Under Data Scarcity
Pages 1781 - 1783
Abstract
Social Simulation is one of the most prominent uses of Multiagent Systems, but it requires the costly task of fitting parameters to assure the credibility of the model. As, to date, there is no consensus on how to calibrate parameters of agent-based models, we have investigated other knowledge domains to develop an efficient method for this task. Our proposal is based on the definition of a surrogate model, that reduces search space dimension. We have tested our method in the housing market scenario, using real data. We achieved satisfactory results, that corroborate the idea that it is important to reduce the search space for an efficient parameter calibration.
References
[1]
Benoit Calvez and Guillaume Hutzler. 2005. Automatic tuning of agent-based models using genetic algorithms. In International Workshop on Multi-Agent Systems and Agent-Based Simulation. Springer, 41--57.
[2]
Raphaël Duboz, David Versmisse, Morgane Travers, Eric Ramat, and Yunne-Jai Shin. 2010. Application of an evolutionary algorithm to the inverse parameter estimation of an individual-based model. Ecological modelling, Vol. 221, 5 (2010), 840--849.
[3]
FIPE-ZAP. 2018. Variacao do índice FIPE-ZAP. (2018). http://fipezap.zapimoveis.com.br.
[4]
Jay W Forrester. 1994. System dynamics, systems thinking, and soft OR. System Dynamics Review, Vol. 10, 2--3 (1994), 245--256.
[5]
Nikolaus Hansen. 2006. The CMA evolution strategy: a comparing review. Towards a new evolutionary computation. Springer, 75--102.
[6]
Zach Lewkovicz, Daniel Domingue, and Jean-Daniel Kant. 2009. An agent-based simulation of the French labour market: studying age discrimination. In The 6th Conference of the European Social Simulation Association, eds., Bruce Edmonds and Nigel Gilbert,(9 2009) .
[7]
J. H. Miller and S. E. Page. 2007. Complex Adaptive Systems. Princeton University Press, New Jersey, United States.
[8]
Matteo G Richiardi, Roberto Leombruni, Nicole J Saam, and Michele Sonnessa. 2006. A common protocol for agent-based social simulation. Journal of artificial societies and social simulation, Vol. 9 (2006).
[9]
Alex Rogers and Peter Von Tessin. 2004. Multi-objective calibration for agent-based models. In Proceedings of 5th Workshop on Agent-Based Simulation .
[10]
Meghendra Singh, Achla Marathe, Madhav V Marathe, and Samarth Swarup. 2018. Behavior Model Calibration for Epidemic Simulations. In Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. International Foundation for Autonomous Agents and Multiagent Systems, 1640--1648.
[11]
John D. Sterman. 2000. Business Dynamics - Systems thinking and modeling for a complex world. Irwin McGraw-Hill, United States.
[12]
Albert Tarantola. 2005. Inverse problem theory and methods for model parameter estimation .siam.
[13]
Jan C Thiele, Winfried Kurth, and Volker Grimm. 2014. Facilitating parameter estimation and sensitivity analysis of agent-based models: A cookbook using NetLogo and R. Journal of Artificial Societies and Social Simulation, Vol. 17, 3 (2014), 11.
[14]
Rohit Tripathy and Ilias Bilionis. 2018. Deep UQ: Learning deep neural network surrogate models for high dimensional uncertainty quantification. arXiv preprint arXiv:1802.00850 (2018).
[15]
Paul Windrum, Giorgio Fagiolo, and Alessio Moneta. 2007. Empirical validation of agent-based models: Alternatives and prospects. Journal of Artificial Societies and Social Simulation, Vol. 10, 2 (2007), 8.
Index Terms
- Using Surrogate Models to Calibrate Agent-based Model Parameters Under Data Scarcity
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Published In
May 2019
2518 pages
ISBN:9781450363099
- General Chairs:
- Edith Elkind,
- Manuela Veloso,
- Program Chairs:
- Noa Agmon,
- Matthew E. Taylor
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Publisher
International Foundation for Autonomous Agents and Multiagent Systems
Richland, SC
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Published: 08 May 2019
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AAMAS '19
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AAMAS '19: International Conference on Autonomous Agents and Multiagent Systems
May 13 - 17, 2019
Montreal QC, Canada
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AAMAS '19 Paper Acceptance Rate 193 of 793 submissions, 24%;
Overall Acceptance Rate 1,155 of 5,036 submissions, 23%
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