International Journal Papers

Agent Modeling Bae, J. W., Bae, S. W., Moon, I. C., & Kim, T. G. (2016). Efficient Flattening Algorithm for Hierarchical and Dynamic Structure Discrete Event Models. ACM Transactions on Modeling and Computer Simulation (TOMACS), 26(4), 25.

2015.11.19 11:06

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Bae, J. W., Bae, S. W., Moon, I. C., & Kim, T. G. (2016). Efficient Flattening Algorithm for Hierarchical and Dynamic Structure Discrete Event Models. ACM Transactions on Modeling and Computer Simulation (TOMACS), 26(4), 25.

Abstract:

Discrete event models are widely used to replicate, analyze, and understand complex systems. DEVS (Discrete Event System Specification) formalism enables hierarchical modeling, so it provides an efficiency in the model development of complex models. However, the hierarchical modeling incurs prolonged simulation executions due to indirect event exchanges through the model hierarchy. Although direct event paths are applied to mitigate this overhead, the situation becomes even worse when a model changes its structures during simulation execution, called a dynamic structure model. This article suggests Coupling Relation Graph (CRG) and Strongly Coupled Component (SCC) concepts to improve hierarchical and dynamic structure DEVS simulation execution. CRG is a directed graph representing DEVS model structure, and SCC is a group of connected components in a CRG. Using CRG and SCC, this article presents (1) how to develop CRG from a DEVS model and (2) how to construct and update direct event paths with respect to dynamic structural changes. In particular, compared to the previous works, the proposed method focuses on the reduction of the updating costs for the direct event paths. Through theoretical and empirical analyses, this article shows that the proposed method significantly reduces the simulation execution time, especially when a simulation model contains lots of components and changes its model structures frequently. We expect that the proposed method would support the faster simulation executions of complex hierarchical and dynamic structure models.

Source Webpage :

http://dl.acm.org/citation.cfm?id=2875356

Bibtex:

@article{Bae:2016:EFA:2892241.2875356,
 author = {Bae, Jang Won and Bae, Sang Won and Moon, Il-Chul and Kim, Tag Gon},
 title = {Efficient Flattening Algorithm for Hierarchical and Dynamic Structure Discrete Event Models},
 journal = {ACM Trans. Model. Comput. Simul.},
 issue_date = {March 2016},
 volume = {26},
 number = {4},
 month = feb,
 year = {2016},
 issn = {1049-3301},
 pages = {25:1--25:25},
 articleno = {25},
 numpages = {25},
 url = {http://doi.acm.org/10.1145/2875356},
 doi = {10.1145/2875356},
 acmid = {2875356},
 publisher = {ACM},
 address = {New York, NY, USA},
 keywords = {DEVS, Flattening algorithm, dynamic structure model, graph-based acceleration, hierarchical model},
}

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No.	Subject
32	Dongjun Kim, Kyungwoo Song, Yoon-Yeong Kim, Yongjin Shin, Wanmo Kang, Il-Chul Moon, Weonyoung Joo, Sequential Likelihood-Free Inference with Neural Proposal, Pattern Recognition Letters, Volume 169, 2023, Pages 102-109
31	Hyungho Na, Jaemyung Ahn, and Il-Chul Moon, "Weapon–Target Assignment by Reinforcement Learning with Pointer Network, " Journal of Aerospacce Information Systems, Vol. 20, No. 1 (2023), pp. 53-59
30	Tae-Sub Yun, Dongjun Kim, Il-Chul Moon, Jang Won Bae, (2022) Agent-Based Model for Urban Administration: A Case Study of Bridge Construction and its Traffic Dispersion Effect, Journal of Artificial Societies and Social Simulation
29	Woo-Seop Yun, Sunggil Ko, Muhyun Byun, Heeyoung Kim, Il-Chul Moon and Tae-Eog Lee, Toward Robust Battle Experimental Design for Command and Control of Mechanized Infantry Brigade, Military Operations Research, Vol. 27, No. 1 (2022), pp. 45-72
28	J. H. Lee, I. -C. Moon and R. Oh, "Similarity Search on Wafer Bin Map Through Nonparametric and Hierarchical Clustering," in IEEE Transactions on Semiconductor Manufacturing, vol. 34, no. 4, pp. 464-474, Nov. 2021, doi: 10.1109/TSM.2021.3102679.
27	Kim, D., Yun, TS., Moon, IC. et al. Automatic calibration of dynamic and heterogeneous parameters in agent-based models. Auton Agent Multi-Agent Syst 35, 46 (2021).
26	Kim, Yoon-Yeong, et al. "Black-Box Expectation–Maximization Algorithm for Estimating Latent States of High-Speed Vehicles." Journal of Aerospace Information Systems 18.4 (2021): 175-192.
25	Joo, W., Lee, W., Park, S., & Moon, I. C. (2020). Dirichlet variational autoencoder. Pattern Recognition, Vol. 107, 107514.
24	Tae-Sub Yun and Il-Chul Moon, "Housing Market Agent-Based Simulation with Loan-To-Value and Debt-To-Income", Journal of Artificial Societies and Social Simulation, Vol. 23, Issue 4, 5, 2020
23	Jang, J.; Shin, S.; Lee, H.; Moon, I.-C. Forecasting the Concentration of Particulate Matter in the Seoul Metropolitan Area Using a Gaussian Process Model. Sensors 2020, 20, 3845.
22	J. W. Bae et al., "Layered Behavior Modeling via Combining Descriptive and Prescriptive Approaches: A Case Study of Infantry Company Engagement," in IEEE Transactions on Systems, Man, and Cybernetics: Systems, vol. 50, no. 7, pp. 2551-2565, July 2020
21	Kim, Dohyung, Hyun-Shik Oh, and Il-Chul Moon. "Black-box Modeling for Aircraft Maneuver Control with Bayesian Optimization." International Journal of Control, Automation and Systems 17.6 (2019): 1558-1568.
20	Shin, S. J., Kang, A., Kim, D., Lee, J., Bae, J. W., & Moon, I. C. (2019). Improving counterfire operations with enhanced command and control structure. Computational and Mathematical Organization Theory, 25(4), 464-498.
19	J. W. Bae et al., "Evaluation of Disaster Response System Using Agent-Based Model With Geospatial and Medical Details," in IEEE Transactions on Systems, Man, and Cybernetics: Systems, vol. 48, no. 9, pp. 1454-1469, Sept. 2018.
18	Il-Chul Moon, Kyungwoo Song, Sang-Hyeon Kim, and Han-Lim Choi, State Prediction of High-speed Ballistic Vehicles with Gaussian Process, International Journal of Control, Automation and Systems, Vol. 16, Issue 3, June 2018, pp 1282-1292
17	Su-Jin Shin, Je-Yong Oh, Sungrae Park, Minki Kim, Il-Chul Moon, Hierarchical prescription pattern analysis with symptom labels, Pattern Recognition Letters, Volume 111, 2018, Pages 94-100
16	Sungrae Park, Doosup Choi, Minki Kim, Wonchul Cha, Chuhyun Kim, Il-Chul Moon, Identifying prescription patterns with a topic model of diseases and medications, Journal of Biomedical Informatics, Volume 75, November 2017, Pages 35-47
15	Su-Jin Shin, and Il-Chul Moon, "Guided HTM: Hierarchical Topic Model with Dirichlet Forest Priors", IEEE Transactions on Knowledge & Data Engineering. vol. 29 no. 2, p. 330-343, Feb., 2017
»	Bae, J. W., Bae, S. W., Moon, I. C., & Kim, T. G. (2016). Efficient Flattening Algorithm for Hierarchical and Dynamic Structure Discrete Event Models. ACM Transactions on Modeling and Computer Simulation (TOMACS), 26(4), 25.
13	Bae, J. W., & Moon, I. C. (2016). LDEF Formalism for Agent-Based Model Development. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 46(6), 793–808.

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