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