This is an advanced graduate course that covers advanced topics in Artificial Intelligence. Topics vary from one offering to the next and are likely to be drawn from the following list: planning, scheduling, games, search, reasoning (constraint-based, model-based, spatial, temporal), knowledge representation, decision-making under uncertainty, reinforcement learning, agents, foundations.
Learning Outcomes
Upon successful completion, students will have the knowledge and skills to:
- Gain both a wide and a deep knowledge of the topic(s) taught in the current instance of the course.
- Improve their skills at navigating through, and critically examining, the scientific literature on the taught topic(s).
