Center for Analysis and Design of Intelligent Agents

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 and explain:

• Where AI came from and what its aims are
• The limitations of contemporary AI methodologies
• The difference between “narrow AI” and general intelligence
• Ongoing next-generation projects in industry and academia
• Architectural requirements for building agents
• The role of cognitive architecture in AI, robotics, and general machine intelligence
• Describe potential solutions to advancing the field of AI
• List key methodological difficulties in building advanced AI systems

Posses the following skills:

• Running existing experimental AI systems
• Programming a GMI-oriented system
• Foresee how AI might evolve over the next few years – even decades – based on a variety of scientific, economic and political assumptions 

Have acquired the following competences:

• Explain key components of some AML/GMI architectures, and how these relate to the creation of truly intelligent machines of the future
• Explain key components of next-gen AI architectures
• Describe the key cognitive processes that lack a scientific theoretical backing
• Explain what is involved in a scientific approach to researching intelligence
• Identify exaggeration and misunderstandings about AI in the media and online forums
• Detect bull#*%^& in articles and general conversations about AI

2025©K.R.Thórisson