القائمة
Evolutionary optimization — genetic algorithm, differential evolution
التثبيت باستخدام Codex أو Claude انسخ هذا Prompt والصقه في Codex أو Claude أو مساعد آخر ليراجع صفحة Skill ويثبّتها لك.
استنادا إلى تصنيف SOC المهني
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