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).
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
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
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).
Bibliography
Course slides are provided in electronic format and annotated during the course.
Assessment of knowledge
Initial assessment / Main session - Tests
Type of assessment | Type of test | Duration (in minutes) | Number of tests | Test coefficient | Eliminatory mark in the test | Remarks |
---|---|---|---|---|---|---|
Integral Continuous Control | Continuous control | 1 |