Slides from all lectures in one file

Introduction to artificial intelligence. Search and metaheuristics: concepts, introduction to single-solution based metaheuristics.

Population-based metaheuristics.

Automated planning: representation, PDDL, use cases

State space planning. Hierarchical task networks.

Plan space planning.

Probability theory (short revision). Bayesian networks. Exact and approximate inference.

Probabilistic reasoning over time.

Utility theory, decision making, sequential decision problems.

Value and policy iteration. Robots, robotic perception. Planning: configuration space.

Robotics: motion planning

Exercises with solutions