Center for Analysis and Design of Intelligent Agents

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[[/public:t-713-mers:mers-26:main|T-713-MERS-2026 Main]] \\
[[/public:t-713-mers:mers-26:lecture_notes|Link to Lecture Notes]]

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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