Comparar métodos

	Programación por Metas Basada en Agentes	Modelado Basado en Agentes (MBA)
Campo	Simulación	Simulación
Familia	Process / pipeline	Process / pipeline
Año de origen	1990s-2000s (hybrid integration)	1970s–1990s (formalized as a field)
Autor original	Charnes, Cooper (GP); Schelling, Holland (ABM foundations)	Thomas Schelling and Robert Axelrod (foundational contributions, 1970s–1990s)
Tipo	Hybrid simulation-optimization	Computational simulation method
Fuente seminal	Charnes, A., Cooper, W. W., & Ferguson, R. O. (1955). Optimal estimation of executive compensation by linear programming. Management Science, 1(2), 138-151.	Axelrod, R. (1997). The Complexity of Cooperation: Agent-Based Models of Competition and Collaboration. Princeton University Press.
Alias	ABGP, Agent-Based GP, ABM-GP, Agent-Driven Goal Programming	ABM, Ajan Tabanlı Modelleme (ABM), multi-agent simulation, individual-based modeling
Relacionados	5	5
Resumen	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.