Methoden vergelijken
Bekijk de geselecteerde methoden naast elkaar; rijen die verschillen zijn gemarkeerd.
| Multi-objective Markov Model× | Markov Model× | |
|---|---|---|
| Vakgebied | Simulatie | Simulatie |
| Familie | Process / pipeline | Process / pipeline |
| Jaar van ontstaan≠ | 2006 | 1906 |
| Grondlegger≠ | Chatterjee, K., Majumdar, R., Henzinger, T. A. (formal; survey: Roijers et al.) | Andrei Markov |
| Type≠ | Stochastic sequential decision model with multiple objectives | Probabilistic state-transition model |
| Oorspronkelijke bron≠ | Roijers, D. M., Vamplew, P., Whiteson, S., & Dazeley, R. (2013). A survey of multi-objective sequential decision-making. Journal of Artificial Intelligence Research, 48, 67–113. DOI ↗ | Norris, J. R. (1997). Markov Chains. Cambridge University Press, Cambridge. ISBN: 9780521633963 |
| Aliassen | MOMDP, Multi-objective MDP, Multi-criteria Markov Decision Process, MO-Markov Model | Markov Chain, Discrete-Time Markov Chain, DTMC, Markov Process |
| Verwant | 5 | 5 |
| Samenvatting≠ | A Multi-objective Markov Model (MOMDP) extends classical Markov Decision Processes to settings where an agent must optimize several reward signals simultaneously. Instead of a single optimal policy, the model produces a Pareto-optimal set of policies, enabling decision-makers to navigate trade-offs between competing goals such as cost, risk, and throughput over time. | A Markov Model represents a system as a finite set of states and specifies the probability of moving from one state to another at each time step. By capturing only the current state — not the full history — it enables tractable analysis of complex dynamic processes across health economics, engineering reliability, operations research, and social-science modeling. |
| ScholarGateGegevensset ↗ |
|
|