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Practices of the artificial intelligence seminar 1 class, where optimization algorithms, evolutionary algorithms and genetic algorithms and others are discussed.

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Practice 1

  • Newton's method
  • Gradient descendent

Practice 2

  • Random search
  • Hill Climbing Adaptative and Hill Climbing Random Mutation

Practice 3

  • Genetic algorithm
  • Elitist genetic algorithm

Practice 4

  • Evolutionary strategies: (1 + 1)-ES, (μ + 1)-ES, (μ + λ)-ES y (μ, λ)-ES

Practice 5

  • Particle Swarm Optimization PSO

Practice 6

  • Diferential evolution, DE Best 1 Bin, DE Current to Rand 1 Exp

Practice 7

  • Artificial Bee Colony

Practice 8

  • Optimization Based on Teaching-Learning

Practice 9

  • Flower Pollination Algorithm

Practice 10

  • Penalties Functions

Excersices

    1. Solution to Systems of Linear Equations
    1. Linear Regression

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Practices of the artificial intelligence seminar 1 class, where optimization algorithms, evolutionary algorithms and genetic algorithms and others are discussed.

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