A scalable multi-node asynchronous implementation of DeepMind’s FunSearch using RabbitMQ.
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Updated
Mar 25, 2026 - Python
A scalable multi-node asynchronous implementation of DeepMind’s FunSearch using RabbitMQ.
A Python package for Large Language Model-Based Automatic Heuristic Design
Companion page for "Artificial Intelligence for Mathematical Reasoning: An Integrated Survey of Language Models, Neuro-symbolic Systems, and Verified Discovery." A curated four-axis index covering MWPs, LLMs and reasoning models, multimodal geometry, Lean theorem proving, and verified discovery (FunSearch, AlphaEvolve, Erdős problems).
An LLM writes trading strategies as code; a search loop calibrates each one and stress-tests it out of sample against a luck baseline, surfacing the few that hold up. Runs on any Yahoo Finance ticker.
Finding better kubernetes schedulers using funsearch with an accelerated simulator
Verifier-gated evolutionary discovery: only proven candidates survive. Zero dependencies.
FunSearch-style evolutionary program discovery for the L-shape Ramsey problem
Autonomous neuro-symbolic research agent synthesizing, verifying, and sandboxing algorithms with FunSearch, CEGIS (Z3), Lean 4 proofs, and Wasmtime JIT
An LLM rewrites your code, a fast Rust scorer grades it on held-out data, the best survives — thousands of iterations a night. Runs as a flat-fee Claude Code session, not a metered Anthropic API loop.
A fully-local engine that finds cross-domain structural bridges between research papers and evolves algorithms along them — 6 GB GPU, zero cloud calls.
NoemaEvolve extends LLM evolutionary program search with RL based reflection and a ReAct style coordination
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