Study-Unit Description

Study-Unit Description


TITLE Affecting Computing and Player Experience

LEVEL 05 - Postgraduate Modular Diploma or Degree Course


DEPARTMENT Institute of Digital Games

DESCRIPTION Affective computing is the multidisciplinary study of emotions via computational lenses. The study involves the phases of emotion elicitation, emotion recognition (feature extraction, feature selection, annotation, classification, regression, preference learning), emotion expression (e.g., facial expression, agent behavioural responses, etc.) and affect-driven adaptation (interaction elements adapt to the user needs/affect).

The study-unit will cover the following topics:

- Theories of emotion (affect and cognition)
- The Affective Loop: key components
- Eliciting Emotion (protocols and approaches)
- Recognizing and Modelling Emotion
    - The model's input
        - Speech, eye gaze, physiology, images, movement/posture
        - Feature Extraction / Selection
    - The model's output (affect annotation / ranks, ratings, ground truth)
    - A taxonomy of modelling approaches
        - Model-based (introduction to popular models of emotion and behaviour)
        - Mode-free
        - A panorama of data-driven approaches to affective modelling
        - Pattern recognition, Classification, Regression, Preference Learning
- Expressing Emotion (via agents and virtual environments)
- Closing the affective loop: Adaptation via agents and virtual environments
- Player Experience Modeling
- Popular application domains: computer games, HCI, health etc.

Study-Unit Aims:

The aims of the unit are to:
- Introduce students to the theories of emotion;
- Introduce students to the methods, algorithms and tools for affect annotation, affect recognition and affect-based adaptation;
- Introduce students to the Player Experience Modeling.

Learning Outcomes:

1. Knowledge & Understanding:

By the end of the study-unit the student will be able to:
- Describe and theorize on the algorithms and domains covered in class;
- Identify tasks that can be tackled through affective computing techniques and select the appropriate technique for the problem under investigation;
- Compare the performance of different methods and reflect on their suitability for a domain;
- Identify uses of affective computing techniques for the modeling of player experience.

2. Skills:

By the end of the study-unit the student will be able to:
- Design and implement efficient affect recognition, modeling and adaptation algorithms;
- Evaluate the algorithms in a commercial-standard application (e.g. game production);

Main Text/s and any supplementary readings:

Picard, Rosalind. Affective Computing. MIT Press, 1997.

Various online articles and textbook chapters provided by the lecturer.

ADDITIONAL NOTES Pre-requisite Qualifications: Bachelor's in Engineering/CS or related fields

STUDY-UNIT TYPE Lecture, Independent Study, Project and Tutorial

Assessment Component/s Resit Availability Weighting
Presentation (10 Minutes) Yes 10%
Oral Examination (20 Minutes) Yes 40%
Report Yes 50%

LECTURER/S Georgios N. Yannakakis

The University makes every effort to ensure that the published Courses Plans, Programmes of Study and Study-Unit information are complete and up-to-date at the time of publication. The University reserves the right to make changes in case errors are detected after publication.
The availability of optional units may be subject to timetabling constraints.
Units not attracting a sufficient number of registrations may be withdrawn without notice.
It should be noted that all the information in the description above applies to study-units available during the academic year 2020/1. It may be subject to change in subsequent years.