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Dominik Magiera, Lukas R\"ohrig, Frank J\"akel
· 1 min read
ResearcharXiv cs.AI
WAMpy: Efficient Synthesis of Prolog Programs in Python
arXiv:2610.03234v1 Announce Type: cross
Abstract: We present WAMpy, a Python framework optimized for synthesizing Prolog programs. Unlike general-purpose Prolog systems, WAMpy targets workloads that repeatedly generate and evaluate small candidate programs. WAMpy compiles Prolog clauses into NumPy array-based WAM instructions and supports partial recompilation of hypotheses against fixed background knowledge. Performance-critical routines are accelerated using Numba just-in-time (JIT) compilation. In a benchmark of repeated compilation-and-evaluation workloads, WAMpy improves end-to-end performance compared with SWI-Prolog accessed from Python using Janus.
Original source
This story was published by arXiv cs.AI and written by Dominik Magiera, Lukas R\"ohrig, Frank J\"akel. SyncAI.news shows a preview; the complete article is on the publisher's site.
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