Artificial Intelligence Fundamentals
Kód | Zakončení | Kredity | Rozsah | Jazyk výuky |
---|---|---|---|---|
BIE-ZUM.21 | Z,ZK | 5 | 2P+2C | anglicky |
- Garant předmětu:
- Pavel Surynek
- Přednášející:
- Pavel Surynek
- Cvičící:
- Pavel Surynek
- Předmět zajišťuje:
- katedra aplikované matematiky
- Anotace:
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Students are introduced to the fundamental problems in the Artificial Intelligence, and the basic methods for their solving. It focuses mainly on the classical tasks from the areas of state space search, multi-agent systems, game theory, planning, and machine learning. Modern soft-computing methods, including the evolutionary algorithms and the neural networks, will be presented as well.
- Požadavky:
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Basic knowledge of statistics and algebra. Programming capabilities.
- Osnova přednášek:
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1. Introduction to Artiffcial Intelligence and its history. Turing test, rational behavior and reasoning.
2. The state space and the heuristic methods for state space exploration.
3. Advanced state space search methods: Hill climbing, Simulated annealing, tabu search, population-based methods.
4. Evolutionary computation techniques. Genetic algorithm, operators of initialization, crossover, mutation, and reproduction.
5. Genetic programming, evolution of tree structures. Crossover and mutation of subtrees.
6. Constraint satisfaction problems and the heuristics for their solving.
7. Automated planning. Planning state space search, plans, and actions. Relaxation and abstraction in planning.
8. Multi-agent system and their architectures. Relations between the world and the agents, agent types, utility functions.
9. Game theory. Games in the normal form, game analysis. Pareto-optimality, Nash equilibrium.
10. Game in the extensive form, methods for searching the game tree. Minimax algorithm, alpha-beta pruning.
11. Introduction to Machine learning and Data mining. Supervised and unsupervised learning. Classification, regression, and cluster analysis.
12. Artificial neural networks. Perceptron networks, activation function, backpropagation algorithm, self-organizing networks.
13. Other computational intelligence methods, modern trends.
- Osnova cvičení:
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1. Interactive tools for artificial intelligence
2. AI problem set 1
3. AI problem set 2
4. Programming assignment 1
5. Consulting assignment 1
6. AI problem set 3
7. AI problem set 4
8. Programming assignment 2
9. Consulting assignment 2
10. AI problem set 5
11. Programming assignment 3
12. Consulting assignment 3
13. Reserved, credit
- Cíle studia:
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The course aims to offer students a survey to the areas of Artificial Intelligence. Its main objective is to present a comprehensive overview of AI problems, rather than examining individual methods in detail.
- Studijní materiály:
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1. Russel S., Norvig P. : Artificial Intelligence: A Modern Approach (4th Edition). Prentice Hall, 2020. ISBN 978-0134610993.
2. Ghallab M., Nau D., Traverso P. : Automated Planning and Acting. Cambridge University Press, 2016. ISBN 978-1107037274.
- Poznámka:
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Information about the course and courseware are available at https://courses.fit.cvut.cz/BI-ZUM/
- Rozvrh na zimní semestr 2024/2025:
- Rozvrh není připraven
- Rozvrh na letní semestr 2024/2025:
- Rozvrh není připraven
- Předmět je součástí následujících studijních plánů:
-
- Bachelor Specialization Computer Engineering, 2021 (povinně volitelný předmět)
- Bachelor Specialization, Information Security, 2021 (VO, povinně volitelný předmět)
- Bachelor Specialization, Software Engineering, 2021 (VO)
- Bachelor Specialization, Computer Science, 2021 (PS)
- Bachelor Specialization, Computer Networks and Internet, 2021 (VO)
- Bachelor Specialization Computer Systems and Virtualization, 2021 (VO)
- Bachelor Specialization, Computer Engineering, Version 2024 (VO, povinně volitelný předmět)