Upper approximating probabilities of convergence in probabilistic\n coherence spaces

We develop a theory of probabilistic coherence spaces equipped with an\nadditional extensional structure and apply it to approximating probability of\nconvergence of ground type programs of probabilistic PCF whose free variables\nare of ground types. To this end we define an adapted version of Krivine\nMachine which computes polynomial approximations of the semantics of these\nprograms in the model. These polynomials provide approximations from below and\nfrom above of probabilities of convergence; this is made possible by extending\nthe language with an error symbol which is extensionally maximal in the model.\n