t3tra-dev

直観主義の命題論理+自然演繹の中で与えられた定理を検証する遺伝的アルゴリズムを用いた証明探索エンジン

19
0
100% credibility
Found Feb 19, 2026 at 19 stars -- GitGems finds repos before they trend. Get early access to the next one.
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AI Analysis
Rust
AI Summary

TsadeEngine is a tool that automatically discovers proofs for theorems in intuitionistic propositional logic using an evolutionary search approach.

How It Works

1
🔍 Discover TsadeEngine

You stumble upon TsadeEngine, a clever tool that automatically solves tricky logic puzzles by finding proofs for mathematical statements.

2
📥 Get it ready

You download and launch the proof finder on your computer, and it's all set up in moments.

3
🎯 Pick your puzzle

Choose a logic theorem from the built-in list, like 'Curry' or 'Flip', that you want to see proved.

4
Start the search
🔬
One puzzle

Focus on proving a single theorem and watch it evolve a solution.

📚
Full collection

Test the entire set of logic puzzles to see success rates across many.

5
Proof appears

You watch as it generates and refines ideas until a perfect proof pops up, complete with pretty symbols.

6
💾 Save your work

Save the smart solution it found to reuse later on similar puzzles.

Puzzles mastered

Celebrate as your logic theorems are proved automatically, unlocking deeper understanding without the grind.

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Star Growth

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AI-Generated Review

What is TsadeEngine?

TsadeEngine is a Rust-built proof search engine that uses genetic algorithms to verify theorems in intuitionistic propositional logic under natural deduction. Feed it a theorem from its built-in corpus—like Curry, Flip, or Comp—and it evolves a proof term, normalizes it, and reports success or failure. CLI commands like `tsade-engine single --theorem Curry --unicode` handle single runs, while `all-corpus` benchmarks dozens of provable and unprovable cases, with save/load for models.

Why is it gaining traction?

It tackles intuitionistic logic where traditional provers struggle, distinguishing provable from unprovable theorems via fitness scores and seeded evolution for reproducibility. Unicode output and model persistence let you iterate fast without retraining. The GA approach feels fresh for proof synthesis, blending search heuristics with parallel Rust evaluation.

Who should use this?

Type theorists prototyping intuitionistic proofs. PL students automating natural deduction exercises from a ready corpus. Researchers benchmarking evolutionary methods against hand-crafted tactics in logic engines.

Verdict

Grab it if you're into Rust and automated reasoning—CLI delivers proofs in seconds for simple cases. But with 19 stars and 1.0% credibility, it's raw: sparse docs, no first-order yet, so fork and contribute rather than productionize.

(198 words)

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