Compara mètodes

	Teoria de la Evidència de Dempster-Shafer	Mapes Cognitius Difusos (FCM)
Camp	Computació tova	Computació tova
Família	Machine learning	Process / pipeline
Any d'origen	1976	1986
Autor original	Arthur P. Dempster & Glenn Shafer	Bart Kosko
Tipus	Uncertainty calculus for combining evidence	Fuzzy causal/feedback network for scenario analysis
Font seminal	Dempster, A. P. (1967). Upper and lower probabilities induced by a multivalued mapping. The Annals of Mathematical Statistics, 38(2), 325–339.	Kosko, B. (1986). Fuzzy cognitive maps. International Journal of Man-Machine Studies, 24(1), 65–75.
Àlies	evidence theory, belief functions, evidential reasoning, Dempster-Shafer kanıt teorisi	FCM, Kosko cognitive map, causal cognitive map, bulanık bilişsel haritalar
Relacionats	4	4
Resum	Dempster-Shafer theory is a mathematical framework for reasoning under uncertainty that generalizes Bayesian probability by representing ignorance explicitly. Instead of forcing a single probability on each hypothesis, it assigns belief mass to sets of hypotheses and derives a belief-plausibility interval, and it provides Dempster's rule for fusing evidence from multiple independent sources. Developed from Arthur Dempster's 1967 work and Glenn Shafer's 1976 monograph, it underpins evidential reasoning and sensor/decision fusion.	A fuzzy cognitive map, introduced by Bart Kosko in 1986, represents a system as a network of concepts connected by signed, weighted causal links, and simulates how the concepts influence one another over time. By combining the intuitive structure of a cognitive map with fuzzy weights and iterative activation, FCMs let experts encode causal knowledge and then run what-if scenarios — making them popular for policy analysis, strategic decision-making, and modelling complex socio-technical systems.