Módszerek összehasonlítása

	Multi-objective Markov Model	Markov-modell
Tudományterület	Szimuláció	Szimuláció
Módszercsalád	Process / pipeline	Process / pipeline
Keletkezés éve	2006	1906
Megalkotó	Chatterjee, K., Majumdar, R., Henzinger, T. A. (formal; survey: Roijers et al.)	Andrei Markov
Típus	Stochastic sequential decision model with multiple objectives	Probabilistic state-transition model
Alapmű	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.	Norris, J. R. (1997). Markov Chains. Cambridge University Press, Cambridge. ISBN: 9780521633963
Alternatív nevek	MOMDP, Multi-objective MDP, Multi-criteria Markov Decision Process, MO-Markov Model	Markov Chain, Discrete-Time Markov Chain, DTMC, Markov Process
Kapcsolódó	5	5
Összefoglaló	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.