After taking the course, diligently attending the classes and doing the assignments, thoroughly reading, and actively participating in discussions, students should be able to:

• Describe how common forms of reasoning relate to next-generation AI systems
• List key reasons for using automated reasoning processes in AI
• Explain how reasoning relates to cumulative learning, autonomous hypothesis generation and autonomous reflection
• Describe state-of-the-art reasoning projects in industry and academia
• Build systems that reason through empirical experimentation
• Use a cutting-edge reasoning framework for implementing a system that reasons and understands
• Understand the difference between autonomic and allonomic AI methodologies
• Understand the relation between reasoning and system autonomy
• Explain how reasoning, cumulative learning, and autonomy can help machines handle novelty