Limits of Computational Learning
نویسنده
چکیده
3, 5, 7, 11, 13, . . . what's next? What general rule (apparently) produces this sequence? Maybe the sequence lists all the odd primes, but what if the next datum is 15? Maybe all odd numbers that are not squares? In this course we will study learning (identi cation) of in nite objects (such as in nite sequences) from nite data (such as initial pieces of the sequence), also known as Inductive Inference. What (collections of) sequences can be learned? What does learning, or identi cation, actually mean? We will discuss and compare several notions of identi cation. The main focus lies on exploring the limits of what can be learned algorithmically.
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