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WAMpy framework accelerates Prolog program synthesis in Python

By PulseAugur Editorial · [1 sources] ·

Researchers have developed WAMpy, a Python framework designed for the efficient synthesis of Prolog programs. This system is particularly suited for tasks involving the repeated generation and evaluation of small candidate programs. WAMpy achieves performance gains by compiling Prolog clauses into NumPy array-based WAM instructions and utilizing Numba for just-in-time compilation of performance-critical routines. Benchmarks indicate that WAMpy outperforms SWI-Prolog when accessed via Python with Janus for workloads involving repeated compilation and evaluation. AI

IMPACT This framework could enhance the efficiency of AI systems that rely on symbolic reasoning and program generation.

RANK_REASON The cluster describes a new research paper detailing a novel framework for program synthesis. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.AI →

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WAMpy framework accelerates Prolog program synthesis in Python

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The cluster describes a new research paper detailing a novel framework for program synthesis. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.AI TIER_1 English(EN) · Dominik Magiera, Lukas R\"ohrig, Frank J\"akel ·

    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 …

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