|
|
|
Apr 19, 2024
|
|
CS 283 - Artificial Intelligence for Game Developers
5.0 Credits
Data structures and algorithms used in computer game AI. Includes a discussion of the two most general aspects of game AI including pathfinding and decision making. Pathfinding topics include grid traversal and search algorithms, pathfinding with A*, and waypoint networks. Decision making topics include finite state machines, scripting, and squad level AI (was CMPSC 283). Prerequisite: CS 132 (was CMPSC 143) or CS 135 (was CMPSC 145) or department permission. CS 161 (was CMPSC 161) and CS 271 (was CMPSC 271) highly recommended.
Course-level Learning Objectives (CLOs)
Upon successful completion of the course, students will be able to:
- Design and implement a program that utilizes Dijkstra’s path finding algorithm to navigate arbitrary maps. [REASON]
- Design and implement a program that utilizes the A* path finding algorithms. [REASON]
- Discuss the history and evolution of path finding. [COMMUNICATE]
- Describe basic path finding methodology. [COMMUNICATE]
- Compare and contrast Dijkstra’s and the A* path finding algorithms. [COMMUNICATE]
- Clearly communicate problem and solution descriptions to peers, and work with peers to jointly solve programming problems. [COMMUNICATE]
Add to Personal Catalog (opens a new window)
|
|
|
