القائمة
Optimize a function using SGD, Adam, PSO, or simulated annealing
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-optimize |
| description | Optimize a function using SGD, Adam, PSO, or simulated annealing |
| disable-model-invocation | true |
Run optimization using the machin workspace algorithms.
When the user asks to optimize, minimize, maximize, find best parameters, or tune hyperparameters.
sgd or adam — Smooth differentiable functions, gradient-basedpso (Particle Swarm) — Multi-modal or noisy landscapes, no gradient neededannealing (Simulated Annealing) — Discrete or combinatorial problems, escapes local minimacargo run -p ix-skill -- optimize --algo <method> --function <fn> --dim <n> --max-iter <iter>
Built-in test functions: sphere, rosenbrock, rastrigin
use ix_optimize::gradient::{sgd, adam};
use ix_optimize::pso::pso_minimize;
use ix_optimize::annealing::simulated_annealing;
use ix_optimize::traits::ClosureObjective;