Comparar métodos
Revisa los métodos seleccionados uno junto a otro; las filas que difieren aparecen resaltadas.
| Programación Dinámica Basada en Agentes× | Programación Dinámica Multiobjetivo× | |
|---|---|---|
| Campo | Simulación | Simulación |
| Familia | Process / pipeline | Process / pipeline |
| Año de origen≠ | 1957 (DP); 1990s onward (ABM integration) | 1957-1975 |
| Autor original≠ | Bellman, R. (DP foundation); Tesfatsion, L. et al. (ABM-DP integration) | Extension of Bellman (1957); formalized by multiple authors from 1970s onward |
| Tipo≠ | Hybrid simulation-optimization | Exact optimization — recursive multi-objective decomposition |
| Fuente seminal | Bellman, R. (1957). Dynamic Programming. Princeton University Press, Princeton, NJ. ISBN: 9780691079516 | Bellman, R. (1957). Dynamic Programming. Princeton University Press, Princeton, NJ. ISBN: 9780691079516 |
| Alias | ABDP, Agent-based DP, Multi-agent dynamic programming, ABM-DP | MODP, Multi-criteria dynamic programming, Vector dynamic programming, Pareto dynamic programming |
| Relacionados | 5 | 5 |
| Resumen≠ | Agent-based dynamic programming (ABDP) embeds Bellman's dynamic programming framework within individual agents of an agent-based model, enabling each agent to solve sequential, multi-stage decision problems using backward induction or value-function iteration. The result is a population of optimizing agents whose interactions generate emergent system-level behavior. | Multi-Objective Dynamic Programming (MODP) extends Bellman's classical dynamic programming to settings where a decision-maker must optimize several competing objectives simultaneously across a sequence of stages. Rather than a single optimal policy, it produces a Pareto-optimal set of policies — each representing a distinct trade-off profile — by propagating vector-valued value functions backward through the state space. |
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