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Artificial intelligence

  • School / Prep

    ENSEIRB-MATMECA

Internal code

EI8IF243

Description

The aim of this course is to understand the opportunities and limits of problem-solving approaches based on one of the major areas of AI (Search, Reasoning, Learning).

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Teaching hours

  • CMLectures9,33h
  • TDTutorial14h

Mandatory prerequisites

Projects will be carried out in Python. A good knowledge of the language is required.
General knowledge of programming and data structures

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Syllabus

- Introduction to AI issues, definition of AI
- Board games, heuristics, real-time decision-making
- Logical reasoning, SAT, Constraints
- Machine learning, Neural Networks, Convolutional Networks

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Further information

This course provides an introduction to the main issues in artificial intelligence, through the study of three major approaches to AI: search algorithms (in the context of board games) and the computation of heuristics, automatic reasoning algorithms, in the context of declarative approaches to problems, and machine learning (restricted to neural networks).

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Bibliography

Course slides are provided in electronic format and annotated during the course.

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Assessment of knowledge

Initial assessment / Main session - Tests

Type of assessmentType of testDuration (in minutes)Number of testsTest coefficientEliminatory mark in the testRemarks
Integral Continuous ControlContinuous control1