Trees and learning
Wolfgang Merkle, Frank Stephan · 1996
We characterize FIN-, EX-and BC-learning, as well as the corresponding notions of team learning, in terms of isolated branches on uniformly strongly recursive sequences of trees.Further, the more restrictive models of FIN-learning and strong-monotonic BC-learning can be characterized in terms of isolated branches on a single tree.We discuss learning with additional information where the learner receives an index for a strongly recursive tree such that the function to be learned is isolated on this tree.We show that EX-learning with this type of additional information is strictly more powerful than EX-learning.