This paper describes a reimplementation of a function induction
algorithm that is part of Peter Andreae's robot procedure learning system NODDY.
Results are given, the implementation is compared to Andreae's version,
and the BACON and COPER systems are compared to both.
The discussion focuses on the representation of knowledge--in particular on the
representation of inverse operators and the induced expression--and the
strength of argument typing.
We are currently acquiring citations for the work deposited into this collection. We recognize the distribution rights of this item may have been assigned to another entity, other than the author(s) of the work.If you can provide the citation for this work or you think you own the distribution rights to this work please contact the Institutional Repository Administrator at firstname.lastname@example.org