Introduction to Artificial Intelligence
General
Code: BSC_IT22
Language: English
Delivery: In person
Prerequisites: -
Workload
- Lectures: 52.0 hours
- Lab: 0.0 hours
- Study: 55.5 hours
- Project: 80.0 hours
Course Content
- Introduction to Artificial Intelligence
- State spaces and problem solving through search
- The search algorithms DFS, BFS, UCS, and iterative deepening
- Informed search. Greedy search algorithms and the A* algorithm
- Adversarial search. The Minimax and Expectimax algorithms and their variants
- Agent utility in search problems
- Non-deterministic search problems and Markov decision processes
- The value iteration, policy evaluation, and policy iteration algorithms
- Reinforcement learning. Model-based and model-free learning
- The temporal-difference learning (TD learning) algorithm and the Q-learning algorithm
- Constraint satisfaction problems
- Backtracking search with arc consistency
- Local search algorithms and their variants
- Introduction to Machine Learning
Learning Outcomes
The aim of the course is to introduce basic concepts of Artificial Intelligence and to develop an understanding of selected methods for solution search, adversarial search, reinforcement learning, and constraint satisfaction problems. An introduction machine learning and basic algorithms, such as linear regression, is also included in the course.
Upon successful completion of the course, the student will be able to understand and apply representative methods from each category in order to solve practical artificial intelligence problems.
Skills
Search, analysis and synthesis of data and information, with the use of the technology
Adaptation to new conditions
Decision-making
Independent work
Team work
Working in an international environment
Working in an interdisciplinary environment
Production of new research ideas
Project planning and management
Respect for difference and multiculturalism
Respect for the natural environment
Showing social, professional and ethical responsibility and sensitivity to gender issues
Criticism and self-criticism
Production of free, creative and inductive thinking