Basic Information
The Course Will Cover Different Approaches to Designing and Modeling Single-robot and Multi-robot Systems. The Tools We Will Explore Are Based in a Variety of Artificial Intelligence (ai) Fields Such As Automatic Planning, Sequential Decision Making Under Uncertainty, Model-based Reasoning, Game Theory, Multi-agent Systems, Reinforcement Learning and More. The Course Will Include Learning The Theoretical Aspects of These Tools As Well As Practical Work With Robots Using The Robotic Settings. Learning Outcomes# at The End of The Course The Studetns Will Be Able To# 1. Analyze and Implement Computational Tools That Will Make Robots Move, Sense, and React Using Different Algorithms. 2. Use a Variety of Artificial Intelligence Approaches to Model Single-agent Settings. 3. Use a Framework of Artificial Intelligence Approaches to Model Multiple Agent Settings. 4. Practically Implement Ai Tools in Robotic Applications.
Faculty: Computer Science
|Undergraduate Studies
|Graduate Studies
Pre-required courses
236501 - Introduction to Artificial Intelligence or 236756 - Introduction to Machine Learning