Abstract
In the standard model of inductive inference, a learner gets as input the graph of a function, and has to discover (in the limit) a program for the function. In this paper, we consider besides the graph also other modes of input such as the complement of the graph, the undergraph and the overgraph of the function. The relationships between these models are studied and a complete picture is obtained. Furthermore, these notions are also explored for learning with oracles, learning in teams and learning in the presence of additional information.
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S. Jain and F. Stephan were supported in part by NUS grant numbers R252-000-212-112 and R252-000-308-112.
E. Martin is jointly appointed at the UNSW and National ICT Australia which is funded by the Australian Government’s Department of Communications, Information Technology and the Arts and the Australian Research Council through Backing Australia’s Ability and the ICT Centre of Excellence Program.
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Jain, S., Martin, E. & Stephan, F. Input-Dependence in Function-Learning. Theory Comput Syst 45, 849–864 (2009). https://doi.org/10.1007/s00224-009-9174-x
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DOI: https://doi.org/10.1007/s00224-009-9174-x