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Mastering AI Development for Human Contexts
The Situated AI minor, available to AI students, covers aspects such as embodiment and interaction with humans

Situated AI is a minor introduced in 2024/25, available only to BSc AI students. Its theme is Situated AI, where the term “situated” covers four aspects such as embodiment and interaction with humans. Specifically, the minor has five courses covering robotics, reinforcement learning, conversational AI, formal logic in AI, and their integration in a project.

The aim of the minor is twofold: 1) to offer a complement to the rest of the AI curriculum that can allow students to deepen their knowledge in specific areas of situated AI; 2) to better equip students with hands-on skills such as robot programming, reinforcement learning and LLMs, among others; and 3) to enable students to gain deeper knowledge and experience into state-of-the-art AI techniques and libraries. We expect this minor to also better contribute to research activities at the VU Amsterdam, and reduce the barrier for Bachelor students to make contributions to real-world research activities.

Related VU master’s programs:

Course overview

  • Introduction to Reinforcement Learning

    • Topics: History and related concepts from psychology, Markov Decision Processes, Bellman equations, Model-free vs. model-based reinforcement learning, exploration/exploitation tradeoff, Q learning, overview of deep RL, applications of RL
    • 6 ECTS
    • Period 1
    • Coordinator: Shujian Yu
  • Conversational AI

    • Topics: Grounding language, understanding conversations, management of dialogues (NLU), mental models, QA, storytelling, large language models, Applications (e.g., chatbot technologies), Embodiment in conversational agents, embodied QA
    • 6 ECTS
    • Period 2
    • Coordinators: Filip Ilievski and Piek Vossen
  • Robotics

    • Contents: Mechanics (forward and inverse kinematics, control and dynamics), Perception (Computer Vision, Odometry, Localization and Mapping), Cognition (Path planning, ML for robotics), Practicals with ROS operating system.
    • 6 ECTS
    • Period 1
    • Coordinators: Kevin Sebastian Luck and Kim Baraka
  • Formal Logic for AI

    • Contents: Logic in AI
    • 6 ECTS
    • Period 2
    • Coordinators: Vera Stebletsova and Patrick Koopman
  • Project Situated AI

    • Contents: weekly assignments and demos covering different areas, including reinforcement learning, natural language processing, and robotics.
    • 6 ECTS
    • Period 3
    • Coordinator: Michel Klein

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