Genetic Algorithms
(อัลกอริทึมทางพันธุกรรม)
Definition
Genetic Algorithms (อัลกอริทึมทางพันธุกรรม) Hard Skill
Genetic Algorithms are optimization techniques inspired by the process of natural selection, used to find approximate solutions to complex problems through iterative evolution of candidate solutions.
Expertise Level
Level 1
Basic
1. Understands the basic concepts and terminology of genetic algorithms.
2. Can explain the principles of selection, crossover, and mutation.
3. Able to implement simple genetic algorithm models using basic programming.
Level 2
Intermediate
1. Can design and tune genetic algorithm parameters for specific problems.
2. Understands the impact of population size, mutation rate, and selection methods.
3. Able to apply genetic algorithms to solve medium complexity optimization problems.
Level 3
Advanced
1. Develops advanced genetic algorithm variants and hybrid models.
2. Optimizes performance by integrating genetic algorithms with other machine learning or optimization techniques.
3. Conducts research or solves highly complex, real-world problems using genetic algorithms.
