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| Agent-Based Goal Programming× | 행위자 기반 모델링 (ABM)× | |
|---|---|---|
| 분야 | 시뮬레이션 | 시뮬레이션 |
| 계열 | Process / pipeline | Process / pipeline |
| 기원 연도≠ | 1990s-2000s (hybrid integration) | 1970s–1990s (formalized as a field) |
| 창시자≠ | Charnes, Cooper (GP); Schelling, Holland (ABM foundations) | Thomas Schelling and Robert Axelrod (foundational contributions, 1970s–1990s) |
| 유형≠ | Hybrid simulation-optimization | Computational simulation method |
| 원전≠ | Charnes, A., Cooper, W. W., & Ferguson, R. O. (1955). Optimal estimation of executive compensation by linear programming. Management Science, 1(2), 138-151. DOI ↗ | Axelrod, R. (1997). The Complexity of Cooperation: Agent-Based Models of Competition and Collaboration. Princeton University Press. DOI ↗ |
| 별칭 | ABGP, Agent-Based GP, ABM-GP, Agent-Driven Goal Programming | ABM, Ajan Tabanlı Modelleme (ABM), multi-agent simulation, individual-based modeling |
| 관련 | 5 | 5 |
| 요약≠ | Agent-Based Goal Programming (ABGP) integrates agent-based simulation with goal programming optimization to model systems where multiple autonomous decision-makers pursue competing, prioritized goals. It enables researchers to study how decentralized, adaptive behavior at the agent level leads to system-level outcomes measured against predefined targets, capturing both emergence and multi-criteria satisfaction simultaneously. | Agent-based modeling (ABM) is a computational simulation method, formalized through the work of Thomas Schelling and Robert Axelrod in the 1970s–1990s, that simulates the behavior of complex systems by specifying and running autonomous agents — individuals, firms, cells, or any bounded entity — whose local interactions with each other and with their environment collectively produce global, system-level patterns that could not be predicted from any single agent's rules alone. |
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