2025/12/01 by Vittorio Cipriani, Cipriani, Vittorio, Dino Rossegger +1
Computer Science · Psychology · #Machine Learning and Algorithms #AI-based Problem Solving and Planning #Child and Animal Learning Development
paper · pdf · doi:10.48550/arxiv.2512.01867
The standard framework for studying learning problems on algebraic structures assumes that the structures in the target family are pairwise nonisomorphic. Under this assumption, the most widely investigated learning criterion--Ex-learning--becomes inherently equivalent to the well-known paradigm of Bc-learning. This paper explores what happens when the nonisomorphism requirement is removed and analyzes the extent to which these two learning criteria remain uniformly equivalent.