상세정보
학술대회
Simulation Framework for Self-Evolving Agent-based Models: A Case Study of Housing Market Model
- 발행일
- 201812
- 출처
- Winter Simulation Conference (WSC) 2018, pp.1120-1131
- 협약과제
- 18HS3200, 점진적 기계학습 기반 자가진화(Self-Evolving) 에이전트 시뮬레이션을 이용한 사회변화 예측분석 기술 개발, 백의현
- 초록
- Agent-based modeling and simulation (ABMS) has been applied to various domain problems. ABM consists of multiple agents and environments and focuses on their interactions. While such characteristics lead to its current popularity, they partially makes hard for the model calibration. Model calibration is generally performed by tuning model parameters, but in the ABM case, its interaction structure should be considered as well due to its huge influences to the results. To resolve this problem, this paper suggests a self-evolving ABMS framework. During the self-evolving process, ABM structure as well as parameters are explored and exploited for the model calibration. In particular, we adopt reconfigurable modeling in the proposed simulation framework, which is derived from Discrete Event System Specification (DEVS) formalism. This paper introduces a housing ABM, and the case study using this model shows that the accuracy of the model prediction was significantly increased through the self-evolving process.
- KSP 제안 키워드
- Agent-Based Modeling and Simulation, Case studies, Discrete Event(DE), Evolving process, Housing Market, Market model, Model Calibration, Model agent, Model parameter, Multiple Agents, Simulation framework