Introduction to Artificial Intelligence

Basic concepts, events, projects, and programming languages that contributed to the development of artificial intelligence.

Intelligent Agents

Introduction to possible agent architectures, the relationship between the agent and the environment.

Local Search

Basics of local search and online search.

Evolutionary Algorithms

Evolutionary algorithms and their applications.

Satisfying constraints

filtrace domén, backtracking, kombinace filtrace a prohledávání.

Neural Networks

Perceptron, basic principles and possibilities of multilayer neural networks, types of networks.

Supervised learning

Supervised learning of neural networks

Deep Neural Networks

Principles of deep neural networks and deep learning. hlubokých neuronových sítí a hlubokého učení.

Tree search

variations of informed and uninformed tree search.

Searching with an adversary

minimax search, alpha-beta pruning.

Markovian decision processes

introduction to MD, policy iteration, value iteration.

Reinforced learning

Monte Carlo, SARSA, Q-learning, deep Q-learning.