Guías Docentes Electrónicas
1. General information
Course:
ARTIFICIAL INTELLIGENCE IN VIDEO GAMES
Code:
42378
Type:
ELECTIVE
ECTS credits:
6
Degree:
406 - UNDERGRADUATE DEGREE IN COMPUTER SCIENCE AND ENGINEERING (AB)
Academic year:
2022-23
Center:
604 - SCHOOL OF COMPUTER SCIENCE AND ENGINEERING (AB)
Group(s):
17 
Year:
4
Duration:
C2
Main language:
English
Second language:
Spanish
Use of additional languages:
English Friendly:
N
Web site:
Bilingual:
N
Lecturer: MIGUEL ANGEL FERNANDEZ GRACIANI - Group(s): 17 
Building/Office
Department
Phone number
Email
Office hours
ESCUELA SUPERIOR DE INGENIERIA INFORMATICA / 1.C.11.
SISTEMAS INFORMÁTICOS
2361
miguel.fgraciani@uclm.es
Ver https://www.esiiab.uclm.es/asig.php?codasig=42378&curso=2022-23

2. Pre-Requisites

It is desirable but not essential, that students have some programming skills. The same way any knowledge in the field of artificial intelligence will be suitable for achievement of the subject

3. Justification in the curriculum, relation to other subjects and to the profession

This Subject within the degree programe, relationship whit other subjects and wiht the CS profession. The world of video games has an important place in today's society.  So much so that their level of business is greater even than that of other types of entertainment such as film. There is therefore a great need for experts in this domain. In the development process of a video game, the component associated with the behavior of its elements, requires knowledge of artificial intelligence techniques. Much of videogame programmers deal with this type of resource. This course contributes to the formation of this profile of  professionals.


4. Degree competences achieved in this course
Course competences
Code Description
CM04 Ability to know the fundamentals, paradigms, and techniques of intelligent systems, and analyse, design, and build systems, services, and digital, applications which could use such techniques in any application context.
CM06 Ability to develop and assess interactive systems, and present complex information and its application in the solution of problems with the design of person-computer interaction.
SIS05 Creativity.
SIS07 Knowledge about other cultures and customs.
5. Objectives or Learning Outcomes
Course learning outcomes
Description
Identification of the problems that arise during the development of video games and that can be solved using artificial intelligence techniques.
Improvement of communication skills of the student in English language
Useof packages and libraries for third-party graphics in the development of graphic applications.
Additional outcomes
Description
Understand the problems associated with Artificial Intelligence related to videogames and know how to solve it at a conceptual and programming level
6. Units / Contents
  • Unit 1: Introduction
  • Unit 2: Video Games classification
  • Unit 3: Basic concepts
  • Unit 4: Learning
  • Unit 5: Basic behavior
  • Unit 6: Search tachniques
  • Unit 7: Rule based systems
  • Unit 8: Case based reasoning
  • Unit 9: Connectionism
  • Unit 10: Evolutionary computation
  • Unit 11: Agents
  • Unit 12: Evolutionary behavior
  • Unit 13: Future possibilities
7. Activities, Units/Modules and Methodology
Training Activity Methodology Related Competences ECTS Hours As Com Description
Class Attendance (theory) [ON-SITE] Lectures CM04 CM06 0.6 15 Y N The teacher will explain the basic fundamentals of the subject
Workshops or seminars [ON-SITE] Other Methodologies CM04 CM06 0.6 15 Y N The different technologies associated with the subject are analyzed and tested (HTML, XML, Javascript, Ajax, PHP, unity, etc.)
Class Attendance (practical) [ON-SITE] Project/Problem Based Learning (PBL) CM04 CM06 0.72 18 Y N The students work in person in the development of a project for the subject
In-class Debates and forums [ON-SITE] Debates CM04 CM06 SIS05 SIS07 0.32 8 Y N Students discuss with their classmates the solutions adopted with respect to their course work
Project or Topic Presentations [ON-SITE] Workshops and Seminars CM04 CM06 SIS05 0.08 2 Y N Students present the project made throughout the course
Analysis of articles and reviews [OFF-SITE] Self-study CM04 CM06 SIS07 0.6 15 Y N The students analyze the bibliography and documentation associated with the concepts of the subject
Analysis of articles and reviews [OFF-SITE] Group Work CM04 CM06 SIS05 SIS07 0.6 15 Y N Students work together with their classmates in the analysis of the bibliography and documentation associated with the subject
Writing of reports or projects [OFF-SITE] Group Work CM04 CM06 SIS05 2 50 Y N Students perform, along with their group of practices, the course work of the subject
Practicum and practical activities report writing or preparation [OFF-SITE] Group Work CM04 CM06 SIS05 0.4 10 Y N The students, perform as a group, the memory associated with the course work of the subject
Final test [ON-SITE] Self-study CM04 CM06 SIS05 SIS07 0.08 2 Y N The students take the exam corresponding to the concepts exposed throughout the course
Total: 6 150
Total credits of in-class work: 2.4 Total class time hours: 60
Total credits of out of class work: 3.6 Total hours of out of class work: 90

As: Assessable training activity
Com: Training activity of compulsory overcoming (It will be essential to overcome both continuous and non-continuous assessment).

8. Evaluation criteria and Grading System
Evaluation System Continuous assessment Non-continuous evaluation * Description
Practicum and practical activities reports assessment 25.00% 0.00%
Final test 10.00% 100.00%
Theoretical papers assessment 10.00% 0.00%
Progress Tests 15.00% 0.00%
Laboratory sessions 20.00% 0.00%
Oral presentations assessment 20.00% 0.00%
Total: 100.00% 100.00%  
According to art. 6 of the UCLM Student Evaluation Regulations, it must be provided to students who cannot regularly attend face-to-face training activities the passing of the subject, having the right (art. 13.2) to be globally graded, in 2 annual calls per subject , an ordinary and an extraordinary one (evaluating 100% of the competences).

Evaluation criteria for the final exam:
  • Continuous assessment:
    Assessment Criteria in the regular exam session. Student assessment is done mainly by the development of course work. Tambien se tomara en cuenta, la nota obtenida en el examen correspondiente a los conceptos de la asignatura, student participation in debates and exhibitions, and the contribution of concepts to work, both for its workgroup, and the rest of the work than the other groups performed during the course. The evaluable activities are normally carried out in groups.
  • Non-continuous evaluation:
    Evaluation criteria not defined

Specifications for the resit/retake exam:
Assessment Criteria in the extra session. The work must be equal to the ordinary call, and also demands a presence test.
Specifications for the second resit / retake exam:
Assessment Criteria in the special sessionfor completion of studies. The work must be equal to the ordinary call, and also demands a presence test.
9. Assignments, course calendar and important dates
Not related to the syllabus/contents
Hours hours
Workshops or seminars [PRESENCIAL][Other Methodologies] 15
Class Attendance (practical) [PRESENCIAL][Project/Problem Based Learning (PBL)] 20
Project or Topic Presentations [PRESENCIAL][Workshops and Seminars] 2
Analysis of articles and reviews [AUTÓNOMA][Self-study] 7
Analysis of articles and reviews [AUTÓNOMA][Group Work] 7
Writing of reports or projects [AUTÓNOMA][Group Work] 50
Practicum and practical activities report writing or preparation [AUTÓNOMA][Group Work] 8
Final test [PRESENCIAL][Self-study] 2

Unit 1 (de 13): Introduction
Activities Hours
Class Attendance (theory) [PRESENCIAL][Lectures] 1
In-class Debates and forums [PRESENCIAL][Debates] .5
Analysis of articles and reviews [AUTÓNOMA][Self-study] .5
Analysis of articles and reviews [AUTÓNOMA][Group Work] .5

Unit 2 (de 13): Video Games classification
Activities Hours
Class Attendance (theory) [PRESENCIAL][Lectures] 1
In-class Debates and forums [PRESENCIAL][Debates] .5
Analysis of articles and reviews [AUTÓNOMA][Self-study] .5
Analysis of articles and reviews [AUTÓNOMA][Group Work] .5

Unit 3 (de 13): Basic concepts
Activities Hours
Class Attendance (theory) [PRESENCIAL][Lectures] 2
In-class Debates and forums [PRESENCIAL][Debates] 1.5
Analysis of articles and reviews [AUTÓNOMA][Self-study] 1.5
Analysis of articles and reviews [AUTÓNOMA][Group Work] 1.5

Unit 4 (de 13): Learning
Activities Hours
Class Attendance (theory) [PRESENCIAL][Lectures] 1
In-class Debates and forums [PRESENCIAL][Debates] .5
Analysis of articles and reviews [AUTÓNOMA][Self-study] .5
Analysis of articles and reviews [AUTÓNOMA][Group Work] .5

Unit 5 (de 13): Basic behavior
Activities Hours
Class Attendance (theory) [PRESENCIAL][Lectures] 1
In-class Debates and forums [PRESENCIAL][Debates] .5
Analysis of articles and reviews [AUTÓNOMA][Self-study] .5
Analysis of articles and reviews [AUTÓNOMA][Group Work] .5

Unit 6 (de 13): Search tachniques
Activities Hours
Class Attendance (theory) [PRESENCIAL][Lectures] 1
In-class Debates and forums [PRESENCIAL][Debates] .5
Analysis of articles and reviews [AUTÓNOMA][Self-study] .5
Analysis of articles and reviews [AUTÓNOMA][Group Work] .5

Unit 7 (de 13): Rule based systems
Activities Hours
Class Attendance (theory) [PRESENCIAL][Lectures] 1
In-class Debates and forums [PRESENCIAL][Debates] .5
Analysis of articles and reviews [AUTÓNOMA][Self-study] .5
Analysis of articles and reviews [AUTÓNOMA][Group Work] .5

Unit 8 (de 13): Case based reasoning
Activities Hours
Class Attendance (theory) [PRESENCIAL][Lectures] 1
In-class Debates and forums [PRESENCIAL][Debates] .5
Analysis of articles and reviews [AUTÓNOMA][Self-study] .5
Analysis of articles and reviews [AUTÓNOMA][Group Work] .5

Unit 9 (de 13): Connectionism
Activities Hours
Class Attendance (theory) [PRESENCIAL][Lectures] 1
In-class Debates and forums [PRESENCIAL][Debates] .5
Analysis of articles and reviews [AUTÓNOMA][Self-study] .5
Analysis of articles and reviews [AUTÓNOMA][Group Work] .5

Unit 10 (de 13): Evolutionary computation
Activities Hours
Class Attendance (theory) [PRESENCIAL][Lectures] 1
In-class Debates and forums [PRESENCIAL][Debates] .5
Analysis of articles and reviews [AUTÓNOMA][Self-study] .5
Analysis of articles and reviews [AUTÓNOMA][Group Work] .5

Unit 11 (de 13): Agents
Activities Hours
Class Attendance (theory) [PRESENCIAL][Lectures] 1
In-class Debates and forums [PRESENCIAL][Debates] .5
Analysis of articles and reviews [AUTÓNOMA][Self-study] .5
Analysis of articles and reviews [AUTÓNOMA][Group Work] .5

Unit 12 (de 13): Evolutionary behavior
Activities Hours
Class Attendance (theory) [PRESENCIAL][Lectures] 1
In-class Debates and forums [PRESENCIAL][Debates] .5
Analysis of articles and reviews [AUTÓNOMA][Self-study] .5
Analysis of articles and reviews [AUTÓNOMA][Group Work] .5

Unit 13 (de 13): Future possibilities
Activities Hours
Class Attendance (theory) [PRESENCIAL][Lectures] 2
In-class Debates and forums [PRESENCIAL][Debates] 1
Analysis of articles and reviews [AUTÓNOMA][Self-study] 1
Analysis of articles and reviews [AUTÓNOMA][Group Work] 1

Global activity
Activities hours
General comments about the planning: This course schedule is APROXIMATE. It could vary throughout the academis course due to teaching needs, bank holidays, etc.. A weekly schedule will be properly detailed and updated on the online platform (Campus Virtual). Note that all the lectures, practice sessions, exams and activities performed in the bilingual groups will be entirely taught in English. Classroom teaching is organized in three weekly classes of 1.5 hours each.
10. Bibliography and Sources
Author(s) Title Book/Journal Citv Publishing house ISBN Year Description Link Catálogo biblioteca
The subject requires multiple consultations on the web http://www.google.es/  
Game AI Pro 3. Collected Wisdom of Game AI Professionals Steve Rabin 13 978 1 4987 4258 0 2017  
 
Brian Beuken The Fundamentals of C/C++ Game programming CRC Press 13 978 1 4987 8874 8 2018  
Ian Millington Artificial Intelligence for games San Francisco Elsevier 13:978-0-12-497782-2 2006  
Jose Mira Mira Aspectos básicos de la Inteligencia Artificial Sanz y Torres 1995 Libro de Inteligencia Artificial  
Stuart Russell & Peter Norvig Inteligencia Artificial. Un enfoque moderno Prentice Hall 1996 Libro de Inteligencia Artificial  



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