Artificial Intelligence  
General Course Information  
Edirlei Soares de Lima  
Artificial Intelligence  
Professor: Edirlei Soares de Lima  
B.Sc. in Computer Science UnC  
M.Sc. in Computer Science UFSM  
Ph.D. in Computer Science PUC-Rio  
Teaching Experience: PUC-Rio, UNIRIO, UERJ, IADE-UE  
Game Development Experience:  
Game Engines: RPG Builder, 3D Game Builder;  
Research Projects: most are related with Logtell (;  
Games: Krimson (Best Game Award at SBGames 2010 Indie Game Development  
Festival), and several other prototype games.  
More Information:  
What is Artificial Intelligence?  
Artificial intelligence (AI) is about making computers able to  
perform the thinking tasks that humans and animals are  
capable of.  
o Computers are very good at:  
arithmetic, sorting, searching, play  
some board games better than  
humans, ...  
o Computers are not very good at:  
recognizing familiar faces, speaking  
our own language, deciding what to  
do next, being creative, ...  
What is Game AI?  
While academic AI concerns solving problems optimally, game  
AI is all about entertaining players.  
Complexity Fallacy: it is a common mistake to think that complex game  
AI equals better character behavior.  
Illusion of Intelligence: the player believes an agent is intelligent, then  
it is intelligent.  
Perception Window: most players will only come across some  
characters and enemies for a short time.  
Artificial Intelligence  
Games Development AI: learn common and fundamental  
artificial intelligence concepts and techniques.  
Module Content:  
. Introduction to Artificial Intelligence;  
. Pathfinding;  
. Finite State Machines;  
. Steering Behaviors for Autonomous Agents;  
. Automated Planning;  
. Randomness, Probability, and Genetic Algorithms;  
. Sensor Systems;  
. Behavior Trees;  
. Machine Learning.  
Active and experiential learning:  
Theoretical concepts;  
Practical examples;  
Implementation exercises;  
Game framework: Unity 2021.2.x  
Semester’s PBL team project:  
Implementation of the game AI using the techniques learned during  
the course.  
Continuous Assessment:  
[70%] Intermediate assessment:  
[60%] Individual assignments on the concepts learned;  
[40%] 1st and 2nd intermediate deliveries of the semester’s PBL team  
[30%] End of term assessment:  
[100%] Final delivery of the team project (within the semester’s PBL team  
project) with individual discussion and report.  
Final Assessment:  
[100%] Practical exam on the concepts learned.  
Project Deliveries:  
1st delivery: identification of the AI necessities:  
Definition of the enemies/NPCs that require AI;  
Description of the desired behaviors for the enemies/NPCs;  
Identification of the AI techniques needed;  
2nd delivery: working prototype with basic AI:  
Implementation of the AI for the main enemies/NPCs;  
3rd delivery: final version with full implementation of the AI:  
Full implementation and integration of the AI in the game;  
Individual report about the artificial intelligence methods used in the project.  
Millington, I., Funge, J. (2009). Artificial  
Intelligence for Games (2nd ed.). CRC Press. ISBN:  
Buckland, M. (2004). Programming Game AI by  
Example. Jones & Bartlett Learning. ISBN: 978-1-  
Russell, S. and Norvig, P. (2009). Artificial  
Intelligence: A Modern Approach (3rd ed.).  
Prentice-Hall. ISBN: 0-13-604259-7.  
Artificial Intelligence  
Canvas: Artificial Intelligence  
Course webpage: