Learning domain knowledge to improve theorem proving [chapter]

Jörg Denzinger, Stephan Schulz
1996 Lecture Notes in Computer Science  
We present two learning inference control heuristics for equational deduction. Based on data about facts that contributed to previous proofs, evaluation functions learn to select equations that are likely to be of use in new situations. The rst evaluation function works by symbolic retrieval of generalized patterns from a knowledge base, the second function compiles the knowledge into abstract term evaluation trees. We analyze the performance of the two heuristics on a set of examples and
more » ... trate their usefulness. We also show that these strategies are well suited for cooperation in the framework of the knowledge based distribution method teamwork.
doi:10.1007/3-540-61511-3_69 fatcat:qh5stt4rfzdevepn27rbda5rku