MULTIMEDIA SYSTEMS

MULTIMEDIA SYSTEMS

_
iten
Code
72584
ACADEMIC YEAR
2017/2018
CREDITS
5 credits during the 2nd year of 8732 Electronic Engineering (LM-29) GENOVA
SCIENTIFIC DISCIPLINARY SECTOR
ING-INF/01
LANGUAGE
Italian (English on demand)
TEACHING LOCATION
GENOVA (Electronic Engineering)
semester
1° Semester
Teaching materials

OVERVIEW

The focus of this course will be on the use of AI techniques for generating efficient intelligent behavior in games, with a special attention on improving game play experience.

AIMS AND CONTENT

LEARNING OUTCOMES

  • Identify tasks that can be tackled using AI techniques.
  • Select the appropriate AI technique for the problem under investigation.
  • Design and implement efficient and robust AI algorithms for game tasks
  • Evaluate performance and test the implemented algorithms

Teaching methods

Lectures and practical sessions

SYLLABUS/CONTENT

01 - Introduction [LINK]

02 - Unity Game Engine [LINK]

03 - Path Finding [LINK]

04 - Steering [LINK]

05 - Influence Maps [LINK]

06 - Tree Search [LINK]

07 - Tic-Tac-Toe [LINK]

08 - Reinforcement Learning [LINK]

09 - Dynamic Scripting [LINK]

10 - Conversational Agents [LINK]

GIT repo for source code: https://bitbucket.org/account/user/elioslab/projects/MS

 

RECOMMENDED READING/BIBLIOGRAPHY

  • Lecture notes
  • A. S. Kyaw, «Unity 4. x Game AI Programming». Packt Publishing Ltd.
  • Mat Buckland, «Programming Game AI By Example», Jones & Bartlett Learning.
  • Ian Millington, and John Funge. «Artificial intelligence for games». CRC Press.
  • Steven Rabin «AI Game Programming Wisdom», Vol. 1-4, Charles River Media
  • Stuart Russell and Peter Norvig, «Artificial Intelligence: A Modern Approach» (3a edizione), Prentice Hall
  • Penny de Byl, «Holistic Game Development with Unity»

TEACHERS AND EXAM BOARD

Ricevimento: Appointments. Writing to riccardo.berta@unige.it

Exam Board

RICCARDO BERTA (President)

ALESSANDRO DE GLORIA

FRANCESCO BELLOTTI

LESSONS

Teaching methods

Lectures and practical sessions