Subject: Artificial Inteligence and Game Design

Scientific Area:

Computing

Workload:

80 Hours

Number of ECTS:

7,5 ECTS

Language:

Portuguese

Overall objectives:

1 - The purpose of this course is for graduate students to gain a breadth of understanding in the toolbox of AI approaches employed in digital games. This involves learning/reinforce some basic topics covered in other AI courses, but with a focus on applied knowledge within the context of digital games.
2 - Ability to ident ify, formulate and solve problems.
3 - Understanding of professional and ethical responsibilities.
4 - Recognize the need and have the capacity for learning thro ughout life.

Syllabus:

1 - Introduction, course overview, models of game AI, data structures, representations, complexity, and constraints.
2 - Movement: steering, jumping, coordinated movement, motor control.
3 - Pathfinding: pathfinding graphs, Dijkstra, A*, hierarchical pathfinding , motion planning.
4 - Decision making: decision trees, state machines, behavior trees, goaloriented behavior, scripting.
5 - Tactics and Strategy: wayp oint tactics, tactical analyses, tactical pathfinding, coordinated action.
6 - Learning: decision tree learning, naive bayes, reinforcement learning, artificial neural networks.
7 - Game Playing: game th eory, minimax, transposition tables, opening books and set plays, turn-based strategy games.W48.

Literature/Sources:

Millington, Ian; Kaufmann, Morgan , 2009 , Artificial Intelligence for Games ,
Russel, Stuart; Norvig, Peter , 2010 , Artificial Intelligence: A Modern Approach , Prentice Hall

Assesssment methods and criteria:

Classification Type: Quantitativa (0-20)

Evaluation Methodology:
Lectures. Discussion session. Problem solving. Completion of work on programming and simulation. Tests: the exams aim to assess the theoretical knowledge and theoretical-practical of the students about the subjects taught. Practical work (or projects): the practical work and evaluation projects aimed to assess the ability to apply knowledge of subjects taught. Oral tests: the students presents the practical work or projects and respond to a set of questions, mainly technical, to assess the degree o f knowledge. Evaluation will follow: Theory (40%): 2 x mini-tests; Practicals (50%):Group Project assignment (35%), Individual Project Oral Exam (mandatory pass) (15%); Participation (10%): Not only being there, but being actively involved