Course: AI credits: 5
- Course code
- GTVB22ELAI
- Name
- AI
- Study year
- 2022-2023
- ECTS credits
- 5
- Language
- English
- Coordinator
- S.A. Smith
- Modes of delivery
-
- Tutorial
- Assessments
-
- AI - Other assessment
Learning outcomes
This Elective has five Programme Learning Outcomes.
Programme Learning Outcomes
A1. The student analyses own and others' assumptions and evaluates the relevance of contexts when developing a solution to a complex but structured problem.
A3. The student can construct concepts and relates these to relevant theory and the needs of the users.
D1. The student can apply appropriate evaluation methods to identify improvements.
E3. The student discusses and justifies the added value of a chosen concept or solution in a complex context utilising appropriate means of communication.
F3. The student can experiment with different solutions and reflect upon their impacts and consequences.
Programme Learning Outcomes
A1. The student analyses own and others' assumptions and evaluates the relevance of contexts when developing a solution to a complex but structured problem.
A3. The student can construct concepts and relates these to relevant theory and the needs of the users.
D1. The student can apply appropriate evaluation methods to identify improvements.
E3. The student discusses and justifies the added value of a chosen concept or solution in a complex context utilising appropriate means of communication.
F3. The student can experiment with different solutions and reflect upon their impacts and consequences.
Content
AI and Social Actions Elective. This elective will feature a brief introduction on the field of Artificial Intelligence in general, followed by a more deep dive into how AI is used in game development and game design: pathfinding algorithms, rule/.logic-based systems, behaviour trees, (finite) state machines, social interactions, and more.
The goal of AI in games is not to be the most accurate sharpshooter or the smartest chess player, but to fit the narrative/ environment/ experience that you as a game designer intend to convey.
The elective will focus on the developing social interactions between artificial actors (avatars, game characters, VR-characters or social robots) and humans in a naturalistic manner, using multiple modalities, such as speech, gesture and facial expressions. The students will learn to use a variety of methods involving technology (e.g., ASR, emotion recognition, chatbot, sensing, motion detection, TTS and motion generation), user modelling and research.
The goal of AI in games is not to be the most accurate sharpshooter or the smartest chess player, but to fit the narrative/ environment/ experience that you as a game designer intend to convey.
The elective will focus on the developing social interactions between artificial actors (avatars, game characters, VR-characters or social robots) and humans in a naturalistic manner, using multiple modalities, such as speech, gesture and facial expressions. The students will learn to use a variety of methods involving technology (e.g., ASR, emotion recognition, chatbot, sensing, motion detection, TTS and motion generation), user modelling and research.
Included in programme(s)
School(s)
- School of Communication, Media & IT