Il-Chul Moon

A simple theoretical multiagent model reasons about the criticality of terrorists and regions as terrorist interactions coevolve in geographical and social spaces. Social and spatial relations evolve over time. Estimating their evolutions is important for management, command and control structures, and intelligence analysis research. By knowing future agent social and spatial distributions, an analyst can identify emergent leaders, hot spots, and organizational vulnerabilities. Historically, suc

A simple theoretical multiagent model reasons about the criticality of terrorists and regions as terrorist interactions coevolve in geographical and social spaces. Social and spatial relations evolve over time. Estimating their evolutions is important for management, command and control structures, and intelligence analysis research. By knowing future agent social and spatial distributions, an analyst can identify emergent leaders, hot spots, and organizational vulnerabilities. Historically, suc

Recently, the population of Seoul has been affected by particulate matter in the atmosphere. This problem can be addressed by developing an elaborate forecasting model to estimate the concentration of fine dust in the metropolitan area. We present a forecasting model of the fine dust concentration with an extended range of input variables, compared to existing models. The model takes inputs from holistic perspectives such as topographical features on the surface, chemical sources of the fine dus

Modeling and simulating a real world scenario is fundamentally an abstraction that takes only part of the given scenario into the model. Furthermore, the level of detail in the model, a.k.a. the resolution, plays an important role in the modeling and simulation process. Finally, the abstraction and resolution of the model determine the fidelity of the modeling and simulation, which becomes the ultimate utility for the model users. While abstraction, resolution and fidelity are the corner stones

People often look at social networks as a way of explaining and understanding the design of an organization. The structure of an organization, in terms of workflow, can itself be assessed for feasibility, strength and robustness. Currently, tools for assessing organizations from a social network and from a workflow perspective are completely separate. Thus, we show how you can infer the workflow from the social network and what additional information can be extracted. This enables you to assess

Many disciplines utilize computer games as interactive training simulations.However, their use is often limited to training mechanical skills, and they are not viewed as a sophisticated training tool with which to teach human interactions within organizations and social/organizational skills. Therefore, in this paper we examine how the players of the game America's Army changed their performance, play styles and social positions after one year of game play experience. For the initial investigati

The rapid diffusion of information and opinions through social media, such as web forums and micro-blogs, is affecting the development of crisis situations, such as the Iranian presidential election, the Egyptian protest, and the ROKS Cheonan sinking. Understanding this rapid widespread diffusion, and assessing what information is spreading, what ideas are becoming common, and who is talking about what, is critical for crisis management. This paper presents a computational system for social medi

We conducted the second data analysis with a new game log record dataset and focused on what the optimal team structure is in terms of communication and movement.We utilized regression analyses and correspondence analyses to make the optimal network, and we identified several important features of optimal networks from those analyses.Furthermore we coded 'Network Fitter' and used it to make a computer program figure out the most effective team organization.From the fitting result, we could obtai

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