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Evolutionary optimization — genetic algorithm, differential evolution
Codex または Claude でインストール この Prompt をコピーして Codex、Claude、または他のアシスタントに貼り付けると、Skill ページを確認してインストールできます。
SOC 職業分類に基づく
Test model robustness with adversarial attacks and defenses
Multi-armed bandit simulation — epsilon-greedy, UCB1, Thompson sampling
Benchmark and compare ix algorithm performance
Embedded Redis-like cache with TTL, LRU, pub/sub, and RESP protocol
Category theory primitives — monad laws verification, free-forgetful adjunction
Chaos theory analysis — Lyapunov exponents, bifurcation, attractors, fractals
| name | ix-evolution |
| description | Evolutionary optimization — genetic algorithm, differential evolution |
| disable-model-invocation | true |
Population-based global optimization on benchmark functions.
When the user needs gradient-free global optimization, wants to compare GA vs DE, or is working with non-convex objective functions.
use ix_evolution::genetic::GeneticAlgorithm;
use ix_evolution::differential::DifferentialEvolution;
Tool name: ix_evolution
Parameters: algorithm (genetic/differential), function, dimensions, generations