O_ocw_intsys_21_22_01 - Intelligent Systems

Topic outline

• Select topic Intelligent Systems

  Intelligent Systems

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  • Select activity INTELLIGENT SYSTEMS Course Description In this c...

    INTELLIGENT SYSTEMS

    Course Description

    In this course we focus on search and optimization techniques for solving AI problems and knowledge representation dealing with uncertain.
    We study general high-level procedures (metaheuristics) that are among the most effective solution strategies for solving combinatorial optimization problems in practice. They are designed to solve large-scale optimization problems that cannot be solved in reasonable processing time by the classic combinatorial optimization methods.
    On the other hand, we present the ability of fuzzy rule-based systems to deal with unknown or incompletely specified environments and their applications in real world problems.

  • Select activity Authors: Elisa Guerrero Vazquez  (elisa.guerrer...

    Authors:

    • Elisa Guerrero Vazquez  (elisa.guerrero@uca.es)
    • Andrés Yáñez Escolano
    • María de la Paz Guerrero Lebrero
    • Guillermo Bárcena González

    Computer Sciences Department (University of Cadiz)

  • Select activity Keywords Metaheuristics, Simulated Annealing, Tab...

    Keywords

    Metaheuristics, Simulated Annealing, Tabu Search, Constraint Satisfaction Problems, Genetic Algorithms, Particle Swarm Optimization, Fuzzy Systems, Mandani Inference

  • Select activity Syllabus    Advanced techniques in Search and Opt...

    Syllabus

       Advanced techniques in Search and Optimization

             1.   Constraint Satisfaction Problems

             2.  Metaheuristics based on trajectories

             3.   Metaheuristics based on populations

        Uncertainty

             4.  Fuzzy Systems

    Learning results

    1. Know the basics of Intelligent Systems through the description and identification of optimization and search problems.
    2. Define constraint satisfaction problems, and study techniques and metaheuristics for their resolution.
    3. Know and apply the main metaheuristics based on trajectories, such as simulated annealing and taboo search.
    4. Know and apply the main population-based metaheuristics, such as genetic algorithms and particle clusters.
    5. Know different approaches for managing uncertainty such as Fuzzy systems.

• Select topic 1. Constraint Satisfaction Problems (CSP)

  1. Constraint Satisfaction Problems (CSP)

   1. Constraint Satisfaction Problems

  • Select activity Materials

    Materials

  • Select activity 1 - Constraint Satisfaction Problems

    

    1 - Constraint Satisfaction Problems File
  • Select activity Video: Applications of Graph Colouring

    

    Video: Applications of Graph Colouring URL
  • Select activity Activities and Excercises

    Activities and Excercises

  • Select activity Activity 1.1: Backtracking and the Graph Colouring Problem

    

    Activity 1.1: Backtracking and the Graph Colouring Problem File
  • Select activity Activity 1.2: General Purpose Heuristics

    

    Activity 1.2: General Purpose Heuristics File
  • Select activity Activity 1.3: Heuristics Implementation

    

    Activity 1.3: Heuristics Implementation File
  • Select activity Adjacency Matrix

    

    Adjacency Matrix File
  • Select activity Activity 1.4. Local Search: Tasks and workers

    

    Activity 1.4. Local Search: Tasks and workers File
  • Select activity Self-Assessment

    Self-Assessment

  • Select activity Backtracking Rubric

    

    Backtracking Rubric File
  • Select activity Answers-Graph Colouring Problem

    

    Answers-Graph Colouring Problem File
  • Select activity Self-Assessment Quiz

    

    Self-Assessment Quiz File
  • Select activity References (copia)

    References

  • Select activity Intelligent Systems - Schalkoff (UCA-Library)

    

    Intelligent Systems - Schalkoff (UCA-Library) URL
  • Select activity Artificial Intelligence - Russell & Norvig (UCA-Library)

    

    Artificial Intelligence - Russell & Norvig (UCA-Library) URL
  • Select activity Website: Artificial Intelligence: A Modern Approach

    

    Website: Artificial Intelligence: A Modern Approach URL
• Select topic 2. Trajectory-based Metaheuristics

  2. Trajectory-based Metaheuristics

  2. Trajectory-based Metaheuristics

  • Select activity Materials (copia)

    Materials

  • Select activity 2- Trajectory-based Metaheuristics

    

    2- Trajectory-based Metaheuristics File
  • Select activity Activities and Excercises (copia)

    Activities and Excercises

  • Select activity Activity 2.1: Annealing and Tasks & Workers

    

    Activity 2.1: Annealing and Tasks & Workers File
  • Select activity Activity 2.2: Tabu search & SAT

    

    Activity 2.2: Tabu search & SAT File
  • Select activity Activity 2.3. Comparative study

    

    Activity 2.3. Comparative study File
  • Select activity Self-Assessment

    Self-Assessment

  • Select activity Self-Assessment Quiz

    

    Self-Assessment Quiz File
  • Select activity Solved-Exercise: SAT&Tabu

    

    Solved-Exercise: SAT&Tabu File
  • Select activity References (copia) (copia)

    References

  • Select activity Artificial Intelligence - Russell & Norvig (UCA-Library)

    

    Artificial Intelligence - Russell & Norvig (UCA-Library) URL
  • Select activity Intelligent Systems - Schalkoff (UCA-Library)

    

    Intelligent Systems - Schalkoff (UCA-Library) URL
• Select topic 3. Population-based Metaheuristics

  3. Population-based Metaheuristics

   3. Population-based Metaheuristics

  • Select activity Materials (copia)

    Materials

  • Select activity Unit 3. Population-based Metaheuristics

    

    Unit 3. Population-based Metaheuristics File
  • Select activity Activities and Excercises (copia)

    Activities and Excercises

  • Select activity Activity 3.1: Before Listening

    

    Activity 3.1: Before Listening File
  • Select activity Genetic Algorithms explained in 4 minutes

    

    Genetic Algorithms explained in 4 minutes File
  • Select activity Activity 3.2. Genetic Operators

    

    Activity 3.2. Genetic Operators File
  • Select activity Activity 3.3: CrossoverMethods

    

    Activity 3.3: CrossoverMethods File
  • Select activity Activity 3.4: PSO

    

    Activity 3.4: PSO File
  • Select activity Self-Assessment

    Self-Assessment

  • Select activity U3_GAQuizz

    

    U3_GAQuizz File
  • Select activity References (copia)

    References

  • Select activity How to solve it. Modern Heuristics - Michalewicz, Z. & Fogel D. (UCA-Library)

    

    How to solve it. Modern Heuristics - Michalewicz, Z. & Fogel D. (UCA-Library) URL
  • Select activity Metaheuristics. From design to implementation. El-Ghazali Talbi. (Wiley 2009)

    

    Metaheuristics. From design to implementation. El-Ghazali Talbi. (Wiley 2009) URL
  • Select activity Swarm Intelligence

    

    Swarm Intelligence URL
• Select topic 4. Uncertainty

  4. Uncertainty

  Fuzzy Systems

  • Select activity Materials (copia)

    Materials

  • Select activity Fuzzy Systems

    

    Fuzzy Systems File
  • Select activity Fuzzy Systems - An introduction

    

    Fuzzy Systems - An introduction URL
  • Select activity Activities and Excercises (copia)

    Activities and Excercises

  • Select activity Activity 4.1: Fuzzy Operators & Tipping in a restaurant

    

    Activity 4.1: Fuzzy Operators & Tipping in a restaurant File
  • Select activity Activity 4.2: FISinMatlab

    

    Activity 4.2: FISinMatlab File
  • Select activity Self-Assessment

    Self-Assessment

  • Select activity Temperature Control - Solution

    

    Temperature Control - Solution File
  • Select activity References (copia)

    References

  • Select activity Fuzzy Sets - Zadeh, L.A. (Google Scholar)

    

    Fuzzy Sets - Zadeh, L.A. (Google Scholar) URL
  • Select activity How to solve it. Modern Heuristics - Michalewicz, Z. & Fogel D. (UCA-Library)

    

    How to solve it. Modern Heuristics - Michalewicz, Z. & Fogel D. (UCA-Library) URL
• Select topic Topic 5

  Topic 5
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  Topic 10