Artificial Intelligence  
General Course Information  
Edirlei Soares de Lima  
<edirlei.lima@universidadeeuropeia.pt>  
Artificial Intelligence  
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Professor: Edirlei Soares de Lima  
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Education:  
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B.Sc. in Computer Science – UnC  
M.Sc. in Computer Science – UFSM  
Ph.D. in Computer Science – PUC-Rio  
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Teaching Experience: PUC-Rio, UNIRIO, UERJ, UE-IADE  
Game Experience:  
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Game Engines: RPG Builder, 3D Game Builder (http://www.3dgamebuilder.com.br/);  
Research Projects: most are related with Logtell (http://www.icad.puc-rio.br/~logtell/);  
Games: Krimson (Best Game Award at SBGames 2010 – Indie Game Development  
Festival), and several other prototype games.  
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What is Artificial Intelligence?  
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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?  
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While academic AI concerns solving problems optimally, game  
AI is all about entertaining players.  
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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  
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Games & Apps Development – AI: learn common and  
fundamental artificial intelligence concepts and techniques.  
Module Content:  
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. Introduction to Artificial Intelligence;  
. Pathfinding;  
. Finite State Machines;  
. Automated Planning;  
. Randomness and Probability;  
. Sensor Systems;  
. Steering Behaviors for Autonomous Agents;  
. Behavior Trees;  
. Machine Learning.  
Method  
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Active and experiential learning:  
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Theoretical concepts;  
Practical examples;  
Implementation exercises;  
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Game framework: Unity  
Semester’s PBL team project:  
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Implementation of the game AI using the techniques learned during  
the course.  
Evaluation  
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Continuous Assessment (bipartite):  
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[50%] Intermediate assessment:  
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[60%] Individual exercises on the concepts learned;  
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[40%] Two intermediate deliveries of the team project (within the  
semester’s PBL team project).  
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[50%] End of term assessment:  
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[100%] Final delivery of the team project (within the semester’s PBL team  
project) with individual discussion.  
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Final Assessment:  
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[100%] Individual project development, delivery, and discussion.  
Evaluation  
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Project Deliveries:  
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1st delivery: identification of the AI necessities:  
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Definition of the enemies/NPCs that require AI;  
Description of the desired behaviors for the enemies/NPCs;  
Identification of the AI techniques needed;  
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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:  
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Full implementation and integration of the AI in the game.  
Bibliography  
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Millington, I., Funge, J. (2009). Artificial  
Intelligence for Games (2nd ed.). CRC  
Press. ISBN: 978-0123747310.  
Buckland, M. (2004). Programming Game  
AI by Example. Jones & Bartlett Learning.  
ISBN: 978-1-55622-078-4.  
Russell, S. and Norvig, P. (2009). Artificial  
Intelligence: A Modern Approach (3rd  
ed.). Prentice-Hall. ISBN: 0-13-604259-7.  
Artificial Intelligence  
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Course webpage:  
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http://www.inf.puc-rio.br/~elima/game-ai/  
Contact:  
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edirlei.slima@gmail.com