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	Dempster-Shafer-teorin om evidens	Fuzzy kognitiva kartor (FCM)
Ämnesområde	Soft computing	Soft computing
Familj	Machine learning	Process / pipeline
Ursprungsår	1976	1986
Upphovsperson	Arthur P. Dempster & Glenn Shafer	Bart Kosko
Typ	Uncertainty calculus for combining evidence	Fuzzy causal/feedback network for scenario analysis
Ursprungskälla	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.
Alias	evidence theory, belief functions, evidential reasoning, Dempster-Shafer kanıt teorisi	FCM, Kosko cognitive map, causal cognitive map, bulanık bilişsel haritalar
Närliggande	4	4
Sammanfattning	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.