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Main methods in AI and robotics

This is a classification of techniques and algorithms, giving only keywords …

Learning

Supervised learning

Classification

  • MLP (Multi Layers Perceptron) - PMC (Perceptron multicouches)
    • gradient backpropagation - rétropropagation du gradient
      • stochastic
      • with inertia
      • simulated annealing - recuit simulé
    • newton (second order)
  • RBFNN (Radial Basis Functions Neural Networks)
    • k-means then gradient descent
    • incremental addition of neurons then exact method
  • SVM (Support Vectors Machine)
  • Decision tree - arbre de décision
    • ID3 (based on entropy)
  • k-nearest neighbors - k plus proches voisins

Regression

  • MLP (Multi Layers Perceptron)
  • RBFNN (Radial Basis Functions Neural Network)
  • SVR (Support Vectors Regressor)

Unsupervised learning

Vector quantization / Clustering

Methods Overview [EN]

  • Sequential leader
  • k-means - k-moyennes
  • GNG (Growing Neural Gas)
  • Auto-organizing maps (Kohonen) - cartes auto-organisatrices de Kohonen

Reinforcement learning

Introductory Book [EN]

  • MDP (Markov Decision Processes)
    • Q-learning
    • Value iteration
    • Policy iteration

Planification

Symbolic

  • A*, WA*, IDA*
  • Dijkstra

Logics

Based on STRIPS-like languages (ADL, PDDL).

  • GraphPlan, Stan, IPP, SGP
  • SATplan (Satisfiability Planning)

Others

  • Genetic algorithms - algorithmes génétiques
  • Ant colony - colonies de fourmis

Specific

Path planning

  • Configurations space
  • Potential fields

Perception

Vision

Color Quantization

Image segmentation

Filters

Image Processing Fundamentals [EN]

Edge Detection

  • Canny
    • Canny-Deriche

Sensors fusion

  • Kalman filter
  • Particles filter (bayesian network) - filtrage particulaire
ai/methods.1179344415.txt.gz · Last modified: 2013/09/19 16:43 (external edit)
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