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We investigate natural variations of behaviourally correct learning and explanatory learning—two learning paradigms studied in algorithmic learning theory—that allow us to “learn” equivalence relations on Polish spaces. We give a characterization of the learnable equivalence relations in terms of their Borel complexity and show that the behaviourally correct and explanatory learnable equivalence relations coincide both in uniform and non-uniform versions of learnability and provide a characterization of the learnable equivalence relations in terms of their Borel complexity. We also show that the set of uniformly learnable equivalence relations is $\boldsymbol {\Pi }^1_1$-complete in the codes and study the learnability of several equivalence relations arising naturally in logic as a case study.

We prove a number of results about countable Borel equivalence relations with forcing constructions and arguments. These results reveal hidden regularity properties of Borel complete sections on certain orbits. As consequences they imply the nonexistence of Borel complete sections with certain features.

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LEARNING EQUIVALENCE RELATIONS ON POLISH SPACES

FORCING CONSTRUCTIONS AND COUNTABLE BOREL EQUIVALENCE RELATIONS

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LEARNING EQUIVALENCE RELATIONS ON POLISH SPACES

FORCING CONSTRUCTIONS AND COUNTABLE BOREL EQUIVALENCE RELATIONS