
We extend the notion of anti-unification to cover equational theories and present a method based on regular tree grammars to compute a finite representation of E-generalization sets. We present a framework to combine Inductive Logic Programming and E-generalization that includes an extension of Plotkin's lgg theorem to the equational case. We demonstrate the potential power of E-generalization by three example applications: computation of suggestions for auxiliary lemmas in equational inductive proofs, computation of construction laws for given term sequences, and learning of screen editor command sequences.
49 pages, 16 figures, author address given in header is meanwhile outdated, full version of an article in the "Artificial Intelligence Journal", appeared as technical report in 2003. An open-source C implementation and some examples are found at the Ancillary files
FOS: Computer and information sciences, Computer Science - Logic in Computer Science, Computer Science - Artificial Intelligence, Formal Languages and Automata Theory (cs.FL), Generalization, Learning and adaptive systems in artificial intelligence, Computer Science - Formal Languages and Automata Theory, Equational theory, I.2.3; F.4.1, Logic programming, 68Q32, 68Q45, 68T15, Artificial Intelligence, generalization, Logic in artificial intelligence, I.2.3, inductive logic programming, Inductive logic programming, equational theory, Logic in Computer Science (cs.LO), Artificial Intelligence (cs.AI), Equational classes, universal algebra in model theory, Grammars and rewriting systems, F.4.1
FOS: Computer and information sciences, Computer Science - Logic in Computer Science, Computer Science - Artificial Intelligence, Formal Languages and Automata Theory (cs.FL), Generalization, Learning and adaptive systems in artificial intelligence, Computer Science - Formal Languages and Automata Theory, Equational theory, I.2.3; F.4.1, Logic programming, 68Q32, 68Q45, 68T15, Artificial Intelligence, generalization, Logic in artificial intelligence, I.2.3, inductive logic programming, Inductive logic programming, equational theory, Logic in Computer Science (cs.LO), Artificial Intelligence (cs.AI), Equational classes, universal algebra in model theory, Grammars and rewriting systems, F.4.1
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| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
