Term Space Mapping for DISCOUNT Stephan Schulz We present a learning inference control heuristic implemented for the equational theorem prover DISCOUNT. Information about necessary and superfluous facts generated during successful proof searches ({\em positive\/} and {\em negative} examples) is compiled into a {\em term space map}, a recursive structure describing aspects of the topology of term sets. This map is then used to compute evaluations for facts in new proof searches and thus to guide the proof search. We present results of the learning system on a set of TPTP examples and demonstrate its usefulness.