Non-monotonic Pre-fix Points and Learning

We consider the problem of finding pre-fix points of interactive realizers over arbitrary knowledge spaces, obtaining a relative recursive procedure. Knowledge spaces and interactive realizers are an abstract setting to represent learning processes, that can interpret non-constructive proofs. Atomic pieces of information of a knowledge space are stratified into levels, and evaluated into truth values depending on knowledge states. Realizers are then used to define operators that extend a given state by adding answers and possibly forcing us to remove some: in the learning process states of knowledge change non-monotonically. Existence of a pre-fix point of a realizer is equivalent to the termination of the learning process with some state of knowledge which is free of patent contradictions and such that there is nothing to add. In this paper we generalize our previous results in the case of level 2 knowledge spaces and deterministic operators to the case of ω-level knowledge spaces and of non-deterministic operators.