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DCS-T-720-ATAI-2021 Main

Learning Outcomes DCS-t-720-ATAI-21


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

  • Identify key challenging research questions related to advanced machine learning and (AML) artificial general intelligence (AGI)
    • List methodological difficulties and proposed solutions to building AML/AGI systems
    • Explain key components of some AML/AGI architectures, and how these relate to the creation of truly intelligent machines of the future
  • Students should have a good idea of:
    • The limitations of current AI methodologies
    • How AGI differs from “narrow AI”
    • Some AML/AGI projects in progress
    • What the main requirements are for building complete minds
    • What methodologies are currently available and applicable for building complete minds
    • How software architecture plays a central role in AI, robotics, and AGI
    • How to apply presently-known techniques and methodologies for building complex AI systems
    • Emergence, self-organization, and synergism
    • Students will have had hands-on experience with:
    • Selected machine learning methods, notably reinforcement learning
    • One programming environment targeting AGI
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