상세정보
학술대회
Incremental Self-Evolving Framework for Agent-Based Simulation
- 발행일
- 201612
- 출처
- International Conference on Computational Science and Computational Intelligence (CSCI) 2016, pp.1428-1429
- 협약과제
- 16HS1400, 점진적 기계학습 기반 자가진화(Self-Evolving) 에이전트 시뮬레이션을 이용한 사회변화 예측분석 기술 개발, 백의현
- 초록
- This paper presents a self-evolving scheme of an agent-based simulation to improve agent simulation models to fit real world data in an incremental way without human intervention by machine learning techniques. The proposed method can solve problems of traditional optimization methods of the agent-based simulation by the incremental optimization of agent simulation models. In this paper, we introduce requirements, the structure and internal functions of the self-evolving agent-based simulation framework for social simulation.
- KSP 제안 키워드
- Agent simulation, Machine Learning technique(MLT), Real-world, Simulation Model, Simulation framework, Social Simulation, agent-based simulation, human intervention, optimization methods, self-evolving