title: On the necessity of U-shaped learning.
abstract: A U-shaped curve in a cognitive-developmental trajectory refers to a three-step process: good performance followed by bad performance followed by good performance once again. U-shaped curves have been observed in a wide variety of cognitive-developmental and learning contexts. U-shaped learning seems to contradict the idea that learning is a monotonic, cumulative process and thus constitutes a challenge for competing theories of cognitive development and learning. U-shaped behavior in language learning (in particular in learning English past tense) has become a central topic in the Cognitive Science debate about learning models. Antagonist models (e.g., connectionism versus nativism) are often judged on their ability of modeling or accounting for U-shaped behavior. The prior literature is mostly occupied with explaining how U-shaped behavior occurs. Instead, we are interested in the necessity of this kind of apparently inefficient strategy. We present and discuss a body of results in the abstract mathematical setting of (extensions of) Gold-style computational learning theory addressing a mathematically precise version of the following question: Are there learning tasks that require U-shaped behavior? All notions considered are learning in the limit from positive data. We present results about the necessity of U-shaped learning in classical models of learning as well as in models with bounds on the memory of the learner. The pattern emerges that, for parameterized, cognitively relevant learning criteria, beyond very few initial parameter values, U-shapes are necessary for full learning power! We discuss the possible relevance of the above results for the Cognitive Science debate about learning models as well as directions for future research.
authors: Department of Computer Science, Sapienza University of Rome.
authors: Lorenzo
authors: L
authors: Carlucci
authors: John
authors: J
authors: Case
mesh_terms: D000328:Adult; D002648:Child; D002657:Child Development / Q000502:physiology; D003071:Cognition / Q000502:physiology; D019336:Cognitive Science; D005793:Generalization, Psychological; D006801:Humans; D007802:Language; D007804:Language Development; D007858:Learning; D059032:Learning Curve; D008037:Linguistics / Q000706:statistics & numerical data*; D055641:Mathematical Concepts; D008960:Models, Psychological; D011582:Psychological Theory