Possibility measures are interpreted as upper probabilities that are in par
ticular supremum preserving. We define a possibilistic process as a special
family of possibilistic variables, and show how its possibility distributi
on functions can be constructed. We introduce and study the notions of inne
r and outer regularity for possibility measures. Using these notions, we pr
ove an analogon for possibilistic processes (and possibility measures) of t
he well-known probabilistic Daniell-Kolmogorov theorem, in the important sp
ecial case that the variables assume values in compact spaces, and that the
possibility measures involved are regular. (C) 1999 Elsevier Science B.V.
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