ABSTRACT
We have recently witnessed the proliferation of large-scale behavioral data that can be used to empirically develop agent-based models (ABMs). Despite this opportunity, the literature has neglected to offer a structured agent-based modeling approach to produce agents or its parts directly from data. In this paper, we present initial steps towards an agent-based modeling approach that focuses on individual-level data to generate agent behavioral rules and initialize agent attribute values. We present a structured way to integrate Big Data and machine learning techniques at the individual agent-level. We also describe a conceptual use-case study of an urban mobility simulation driven by millions of geo-tagged Twitter social media messages. We believe our approach will advance the-state-of-the-art in developing empirical ABMs and conducting their validation. Further work is needed to assess data suitability, to compare with other approaches, to standardize data collection, and to serve all these features in near-real time.
- Ankam, V. 2016. Big Data Analytics: Packt Publishing. Google ScholarDigital Library
- Bonabeau, Eric. 2002. "Agent-based modeling: Methods and techniques for simulating human systems." Proceedings of the National Academy of Sciences 99:7280--7287.Google ScholarCross Ref
- Bruch, Elizabeth, and Jon Atwell. 2015. "Agent-Based Models in Empirical Social Research." Sociological methods & research 44 (2):186--221.Google Scholar
- Chen, Jilin, Eben Haber, Ruogu Kang, Gary Hsieh, and Jalal Mahmud. 2010. "Making Use of Derived Personality : The Case of Social Media Ad Targeting."Google Scholar
- Collado, Samer Hassan. 2009. "Towards a Data-driven Approach for Agent-Based Modelling: Simulating Spanish Postmodernisation."Google Scholar
- Ester, Martin, Hans-Peter Krieger, Jörg Sander, and Xiaowei Xu. 1996. "A Density-Based Algorithm for Discovering Clusters in Large Spatial Databases with Noise." Portland, Oregon, 1996.Google Scholar
- Fayyad, Usama, Gregory Piatetsky-Shapiro, and Padhraic Smyth. 1996. "From data mining to knowledge discovery in databases." AI magazine:37--54.Google Scholar
- Gilbert, Nigel. 1999. "Simulation A new way of doing science." American Behavioral Scientist 42 (10):1485--1487.Google Scholar
- Gilbert, Nigel. 2008. Agent-Based Models. Vol. 153. Thousand Oaks, CA, USA: SAGE Publications.Google Scholar
- González, Marta C., César A. Hidalgo, and Albert-László Barabási. 2008. "Understanding individual human mobility patterns." Nature 453 (7196):779--782.Google ScholarCross Ref
- Helbing, Dirk, and Stefano Balietti. 2011. How to Do Agent-Based Simulations in the Future: From Modeling Social Mechanisms to Emergent Phenomena and Interactive Systems Design. Santa Fe Institute.Google Scholar
- Hsieh, Gary, Jilin Chen, Jalal Mahmud, and Jeffrey Nichols. 2014. "You Read What You Value : Understanding Personal Values and Reading Interests." Proceedings of the 32nd annual ACM conference on Human factors in computing systems April:983--986. Google ScholarDigital Library
- Jensen, Thorben, and Émile J. L. Chappin. 2017. "Automating agent-based modeling: Data-driven generation and application of innovation diffusion models." Environmental Modelling & Software 92 (Supplement C):261--268. Google ScholarDigital Library
- Jiang, Shan, Joseph Ferreira, and Marta C. González. 2015. "Activity-Based Human Mobility Patterns Inferred from Mobile Phone Data : A Case Study of Singapore." ACM KDD UrbComp'15.Google Scholar
- Kavak, Hamdi, Jose J. Padilla, Daniele Vernon-Bido, Ross J. Gore, and Saikou Y. Diallo. 2017. "The Spread of Wi-Fi Router Malware Revisited." Spring Simulation Multi-Conference, Virginia Beach, VA, USA, 2017. Google ScholarDigital Library
- Kavak, Hamdi, Daniele Vernon-Bido, and Jose Padilla. 2018. "Fine-Scale Prediction of People's Home Location using Social Media Footprints." SBP-BRIMS, Washington, D.C., USA, In Press.Google Scholar
- Kennedy, Catriona, Georgios Theodoropoulos, Volker Sorge, Edward Ferrari, Peter Lee, and Chris Skelcher. 2007. "AIMSS: An architecture for data driven simulations in the social sciences." 2007.Google Scholar
- Kennedy, William G. 2012. "Modelling Human Behaviour in Agent-Based Models." In, edited by A. J. Heppenstall, A. T. Crooks, L. M. See and M. Batty, 167--179. Springer.Google Scholar
- Kitchin, R., and G. McArdle. 2016. "What makes Big Data, Big Data? Exploring the ontological characteristics of 26 datasets." Big Data & Society 3 (1): 1--10.Google ScholarCross Ref
- Mahmud, Jalal, Jeffrey Nichols, and Clemens Drews. 2014. "Home Location Identification of Twitter Users." arXiv preprint arXiv:1403.2345 xx (xx).Google Scholar
- Malleson, Nick, and Mark H. Birkin. 2012. "Estimating Individual Behaviour from Massive Social Data for An Urban Agent-Based Model." Geosimulation: Modeling Social Phenomena in Spatial Context (September):23--29.Google Scholar
- McKenzie, Frederic D. 2010. "Systems modeling: analysis and operations research." In, 147--180. John Wiley & Sons, Inc.Google Scholar
- Mislove, Alan, Sune Lehmann, Yong-yeol Ahn, Jukka-pekka Onnela, and J. Niels Rosenquist. 2011. "Understanding the Demographics of Twitter Users." Artificial Intelligence:554--557.Google Scholar
- Padilla, Jose J., Saikou Y. Diallo, Hamdi Kavak, Olcay Sahin, and Brit Nicholson. 2014. "Leveraging Social Media Data in Agent-based Simulations." Tampa, FL, 2014.Google Scholar
- Padilla, Jose J., Saikou Y. Diallo, Hamdi Kavak, Olcay Sahin, John S. Sokolowski, and Ross J. Gore. 2016. "Semi-automated initialization of simulations: an application to healthcare." The Journal of Defense Modeling and Simulation: Applications, Methodology, Technology 13 (2): 171--182.Google ScholarCross Ref
- Ryoo, Kyoungmin, and Sue Moon. 2014. "Inferring Twitter user locations with 10 km accuracy." Proceedings of the companion publication of the 23rd international conference on World Wide Web:643--648. Google ScholarDigital Library
- Sajjad, Mazhar, Karandeep Singh, Euihyun Paik, and Chang-Won Ahn. 2016. "A Data-Driven Approach for Agent-Based Modeling: Simulating the Dynamics of Family Formation." Journal of Artificial Societies and Social Simulation 19 (1):9.Google ScholarCross Ref
- Schelling, Thomas C. 1971. "Dynamic models of segregation." The Journal of Mathematical Sociology 1 (2):143--186.Google ScholarCross Ref
- Schneider, Christian M., Vitaly Belik, Thomas Couronné, Zbigniew Smoreda, and Marta C. González. 2013. "Unravelling daily human mobility motifs." Journal of the Royal Society, Interface / the Royal Society 10 (84):20130246--20130246.Google ScholarCross Ref
- Smajgl, Alex, Daniel G. Brown, Diego Valbuena, and Marco G. A. Huigen. 2011. "Empirical characterisation of agent behaviours in socio-ecological systems." Environmental Modelling & Software 26 (7):837--844. Google ScholarDigital Library
- Yang, L. U., and Nigel Gilbert. 2008. "Getting Away From Numbers: Using Qualitative Observation for Agent-Based Modeling." Advances in Complex Systems 11 (02): 175--185.Google ScholarCross Ref
Recommendations
Big Data Processing using Machine Learning algorithms: MLlib and Mahout Use Case
SITA'18: Proceedings of the 12th International Conference on Intelligent Systems: Theories and ApplicationsMachine learning is a field within artificial intelligence that allows machines to learn on their own from existing information to make predictions or/and decisions. There are three main categories of machine learning techniques: Collaborative filtering ...
A Multi-dimensional Comparison of Toolkits for Machine Learning with Big Data
IRI '15: Proceedings of the 2015 IEEE International Conference on Information Reuse and IntegrationBig data is a big business, and effective modeling of this data is key. This paper provides a comprehensive multidimensional analysis of various open source tools for machine learning with big data. An evaluation standard is proposed along with detailed ...
Machine learning on big data
Machine learning (ML) is continuously unleashing its power in a wide range of applications. It has been pushed to the forefront in recent years partly owing to the advent of big data. ML algorithms have never been better promised while challenged by big ...
Comments