Selected Publications


Il-Chul Moon and Kathleen M. Carley, Self-Organizing Social and Spatial Networks under What-if Scenarios, Autonomous Agent and Multi-Agent Systems (AAMAS’07), Honolulu, Hawaii, May 14-18, 2007, pp 127-134

 

Abstract :

 Multi-agent models have been used to simulate complex systems in many domains. In some models, the agents move in a physical/grid space and are constrained by their locations on the spatial space, e.g. Sugarscape. In others, the agents interact in a social multi-dimensional space and are bound to their knowledge and social positions, e.g. Construct. However, many real world problems require a mixed model containing both spatial and social features. This paper introduces such a multi agent system, Construct-Spatial, which simulates agent communication and movement simultaneously. It is an extended version of Construct, which is a multi-agent social model, and its extension is based on a multi-agent grid model, Sugarscape. To understand the impact of this integration of the two spaces, we run virtual experiments and compare the output from the combined space to those from each of the two spaces. The initial analysis reveals that the integration facilitates unbalanced knowledge distribution across the agents compared to the grid-only model and limits agent network connections compared to the social network model without spatial constraints. After the comparisons, we setup what-if scenarios where we varied the type of the threats faced by network and observe their emergent behaviors. From the what-if analyses, we locate the best destabilization scenario and find the propagation of the effects from the spatial space to the social network space. We believe that this model can be a conceptual model for assessing the efficiency and the robustness of team deployments, network node distributions, sensor distributions, etc.

 

@inproceedings{Moon:2007:SSS:1329125.1329430,
 author = {Moon, Il-Chul and Carley, Kathleen M.},
 title = {Self-organizing Social and Spatial Networks Under What-if Scenarios},
 booktitle = {Proceedings of the 6th International Joint Conference on Autonomous Agents and Multiagent Systems},
 series = {AAMAS '07},
 year = {2007},
 isbn = {978-81-904262-7-5},
 location = {Honolulu, Hawaii},
 pages = {252:1--252:8},
 articleno = {252},
 numpages = {8},
 url = {http://doi.acm.org/10.1145/1329125.1329430},
 doi = {10.1145/1329125.1329430},
 acmid = {1329430},
 publisher = {ACM},
 address = {New York, NY, USA},
 keywords = {multi-agent system, network evolution, organizational structure},
} 

 

Source Website : 

 http://dl.acm.org/citation.cfm?id=1329430

No. Subject
16 Kyungwoo Song, Mingi Ji, Sungrae Park, and Il-Chul Moon. Hierarchical Context enabled Recurrent Neural Network for Recommendation. AAAI Conference on Artificial Intelligence (AAAI 2019). Hawaii. Jan. 27-Feb. 1 file
15 Wonsung Lee, Sungrae Park, Weonyoung Joo, and Il-Chul Moon, Diagnosis Prediction via Medical Context Attention Networks Using Deep Generative Modeling, 2018 IEEE International Conference on Data Mining (ICDM'18), Nov. 17-20, Singapore (Short Paper) file
14 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 file
13 Kyungwoo Song, Wonsung Lee, and Il-Chul Moon. Neural Ideal Point Estimation Network. AAAI Conference on Artificial Intelligence (AAAI 2018). New Orleans. Feb 2-7 file
12 Sungrae Park, Jun-Keon Park, Su-Jin Shin, and Il-Chul Moon. Adversarial Dropout for Supervised and Semi-Supervised Learning. AAAI Conference on Artificial Intelligence (AAAI 2018). New Orleans. Feb 2-7 file
11 Wonsung Lee, Kyungwoo Song, and Il-Chul Moon. Augmented Variational Autoencoders for Collaborative Filtering with Auxiliary Information, ACM Conference on Information and Knowledge Management (CIKM 2017), Singapore, Nov 6-10 file
10 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. file
9 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 file
8 Lee, W.S., Lee, Y.M., Kim, H.Y., and Moon, I.-C., 2016. Bayesian Nonparametric Collaborative Topic Poisson Factorization for Electronic Health Records-Based Phenotyping. IJCAI 2016. pp.2544-2552, New York, USA file
7 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. file
6 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. file
5 Lee, W.S., Park, S.R. and Moon, I.-C., 2014. Modeling Multiple Fields of Collective Emotions with Brownian Agent-Based Model. In AAMAS. Paris, France. file
4 Shinjae Yoo, Yiming Yang, Frank Lin, and Il-Chul Moon, Mining Social Networks for Personalized Email Prioritization, ACM SIGKDD Conference, Paris, France, Jun, 28, 2009 file
» Il-Chul Moon and Kathleen M. Carley, Self-Organizing Social and Spatial Networks under What-if Scenarios, Autonomous Agent and Multi-Agent Systems (AAMAS’07), Honolulu, Hawaii, May 14-18, 2007, pp 127-134 file
2 Yiming Yang, Shinjae Yoo, Frank Lin, and Il-Chul Moon, Personalized Email Prioritization Based on Content and Social Network Analysis, IEEE Intelligent Systems, Special Issue on Social Learning, Vol. 25, Issue 4, pp 12-18, Jul/Aug 2010 file
1 Il-Chul Moon and Kathleen M. Carley, Modeling and Simulation of Terrorist Networks in Social and Geospatial dimensions, IEEE Intelligent Systems, Special Issue on Social Computing, Vol. 22, pp 40-49, Sep/Oct. 2007 file