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
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.
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).
Finding better kubernetes schedulers using funsearch with an accelerated simulator
Verifier-gated evolutionary discovery: only proven candidates survive. Zero dependencies.
Autonomous neuro-symbolic research agent synthesizing, verifying, and sandboxing algorithms with FunSearch, CEGIS (Z3), Lean 4 proofs, and Wasmtime JIT
FunSearch-style evolutionary program discovery for the L-shape Ramsey problem
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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