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Basic concepts of Artificial Intelligence

6 ECTS
Bachelor
Czech
Jaroslav Horáček

The course is the first introduction to the broad spectrum of the field of artificial intelligence. The aim of the course is to describe in general terms and illustrate with examples the most important concepts and approaches of artificial intelligence, all without excessive mathematical formalism. These concepts are further elaborated formally and in more depth in the follow-up professional courses in the curriculum of the field. The course serves as a preparatory course for the follow-up professional courses.

Course outline

Intelligence and Artificial Intelligence
different interpretations of the concept of intelligence and artificial intelligence (acting rationally x acting like a human, thinking rationally x thinking like a human), different application claims for "artificial intelligence"
History of AI
basic milestones in the development of the field from the beginning until today
Searching the state space
AI role as a search role (local search, backtracking, CSP, eploration vs. exploration)
Finding the local and global minimum
AI task as an optimization problem
Data, generalisation and approximation
AI task as a generalization and approximation task, generalization of regularities in data
Neuron and neural networks
what can one artificial neuron do, types of neural network connections and their properties, network learning, AI as a blackbox
Logic and reasoning
the role of AI as a correct reasoning, inference, expert system
Machine Learning
with teacher, without teacher, reinforcement learning, role of AI as dimensionality reduction
Language models
from chat bot to chatGPT
Artificial life
evolutionary algorithms, simulation, swarm intelligence, the role of AI as creating new quality
Knowledge model and representation
how AI can use knowledge, how to represent knowledge
"Artificial stupidity"
intelligent solutions where no (artificial) intelligence is needed
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