@article {1416,
	title = {Exploring the behavior space of agent-based simulation models using random forest metamodels and sequential sampling},
	journal = {Simulation Modelling Practice and Theory},
	volume = {92},
	year = {2019},
	pages = {62-81},
	abstract = {<p>Agent-based modeling is an effective way of understanding and analyzing complex adaptive phenomena. In this respect, discovering the relationship between inputs and outputs of agent-based models is the ultimate way of providing insights into understanding the dynamics of the system being modeled. Therefore, there are many approaches in the literature to clarify these relationships including sampling and metamodeling. Emphasizing the weaknesses and disadvantages of current methods, we present a metamodel-guided sequential sampling technique which combines random forests and uncertainty sampling. Experimental results on two well-known agent-based models show that the presented technique yields metamodels of higher accuracy compared to metamodels trained with randomly selected input{\textendash}output data. Contrary to the previous studies emphasizing only the improvement in the metamodel accuracy, we also focus on input parameter combinations selected by the sequential sampling technique, and we observe that sequential sampling is able to capture the boundaries of tipping point behaviors as well as the points exhibiting counter-intuitive behavior, thus, potentially aiding verification, validation, and understanding of agent-based models. Additionally, we propose a novel two-step method for the categorization of the agent-based model outputs prior to metamodel training, which helps the analyst to decide on whether preserving numerical model outputs or continuing the metamodel training procedure with qualitative categorical agent-based model outputs.</p>},
	keywords = {Active learning, Agent-based modeling, Metamodeling, Output categorization, Random forest, Sequential sampling},
	issn = {1569-190X},
	doi = {https://doi.org/10.1016/j.simpat.2018.12.006},
	url = {https://www.sciencedirect.com/science/article/pii/S1569190X18301941},
	author = {Mert Edali and G{\"o}nen{\c c} Y{\"u}cel}
}
@proceedings {nisa1,
	title = {Evaluation of Alternative Dynamic Behavior Representations for Automated Model Output Classification and Clustering},
	journal = {31st International Conference of the System Dynamics Society},
	year = {2013},
	author = {Nisa {\"O}nsel and E. {\"O}nsel and G{\"o}nen{\c c} Y{\"u}cel}
}
@article {Yucel2013,
	title = {Extent of inertia caused by the existing building stock against an energy transition in the Netherlands},
	journal = {Energy and Buildings},
	volume = {56},
	year = {2013},
	pages = {134{\textendash}145},
	keywords = {residential energy consumption},
	issn = {03787788},
	doi = {10.1016/j.enbuild.2012.09.022},
	url = {http://linkinghub.elsevier.com/retrieve/pii/S0378778812004720},
	author = {G{\"o}nen{\c c} Y{\"u}cel}
}
@article {Kwakkel2012,
	title = {An Exploratory Analysis of the Dutch Electricity System in Transition},
	journal = {Journal of the Knowledge Economy},
	year = {2012},
	pages = {1{\textendash}16},
	publisher = {Springer US},
	abstract = {<p>Recent contextual developments constitute a backdrop of change for the Dutch electricity system. Institutional change driven by liberalization, changing economic competitiveness of the dominant fuels, new technologies, and changing end-user preferences regarding electricity supply are some exam- ples of these developments. This paper explores plausible transition trajectories in the face of these developments given technological uncertainty about invest- ment and operating costs, and fuel efficiency of various alternative technolo- gies; political uncertainty about future CO2 abatement policies such as emission trading; and socio-economic uncertainty about fuel prices, investment decisions of suppliers, and load curves. Various alternative developments for these uncertainties are specified. The consequences of each of these alternative developments are assessed using an agent-based model of the Dutch electricity system. The outputs are analyzed using various data-mining and data visualization techniques in order to reveal arch-typical transition trajectories and their conditions for occurring. Policy recommendations are derived from this. The results indicate that most transition trajectories point towards a future energy supply system that is reliant on clean coal and gas. Under the explored uncertainties, only rarely a transition to renewables occurs. The various sustainable energy support programs appear to be ineffective in steering the energy supply system towards a more sustainable mode of functioning across the various uncertainties.</p>},
	keywords = {Electricity supply, Exploratory model, Transitions},
	issn = {1868-7865},
	doi = {10.1007/s13132-012-0128-1},
	url = {http://dx.doi.org/10.1007/s13132-012-0128-1},
	author = {Kwakkel, Jan and G{\"o}nen{\c c} Y{\"u}cel}
}
@article {Yucel2011a,
	title = {Exploratory analysis of the impact of information dynamics on innovation diffusion},
	journal = {Technological Forecasting and Social Change},
	volume = {78},
	number = {2},
	year = {2011},
	pages = {358{\textendash}372},
	publisher = {Elsevier Inc.},
	keywords = {diffusion of innovations, information diffusion, negative word-of-mouth, Simulation model},
	issn = {00401625},
	doi = {10.1016/j.techfore.2010.11.004},
	url = {http://linkinghub.elsevier.com/retrieve/pii/S0040162510002684},
	author = {G{\"o}nen{\c c} Y{\"u}cel and van Daalen, Cornelia}
}
