This course will introduce the basic ideas underlying modelling dynamic decision problems and the methods used to solve them. The course will focus on probabilistic inference, decision making under uncertainty, and multi-agent interaction.
The course helps to develop the mathematical reasoning skills crucial for areas inherently involving uncertainty: artificial intelligence and machine learning, data mining, financial modelling, natural language processing, bioinformatics, web search and information retrieval, algorithm design, system design, network analysis, and more. These skills can serve as the foundation for further study in any application area the student chooses to pursue.

Course objectives

• Learn the basic ideas and techniques underlying design of intelligent rational agents. A specific emphasis will be on the decision-theoretic modelling paradigm.
• Understand state-of-the-art of decision making.
• Learn the basic ideas and techniques underlying design of intelligent rational agents.
• Be able to understand research papers in the field.
• Try out some ideas of your own.