CS 5150 — Game Artificial Intelligence
4 semester hoursGraduateLectureNUpath CENUpath WIusually offered: springtypical days: WBostonTraditional
Offers an overview of classical and modern approaches to artificial intelligence in digital games. Focuses on the creation of believable agents and environments with the goal of providing a fun and engaging experience to a player. Covers player modeling, procedural content generation, behavior trees, interactive narrative, decision-making systems, cognitive modeling, and path planning. Explores different approaches for behavior generation, including learning and rule-based systems. Requires students to complete several individual assignments in these areas to apply the concepts covered in class. Students choose a group final project, which requires a report, to explore one aspect of artificial intelligence for games in further depth. Offers students an opportunity to learn team management and communication. Requires knowledge of algorithms and experience with object-oriented design or functional programming.
Offering history
| Term | Sections | Enrolled | Capacity | Full | Open seats/section |
|---|---|---|---|---|---|
| Spring 2024 | 1 | 21 | 30 | 70% | 9.0 |
| Spring 2025 | 1 | 24 | 24 | 100% | 0.0 |
| Spring 2026 | 1 | 38 | 40 | 95% | 2.0 |
Snapshots from scheduled scrapes — not live seat availability. "Full" can exceed 100% when sections over-enroll.
Meeting times
Share of recent sections by weekday: M 0% · T 0% · W 75% · Th 25% · F 0%
Common patterns: W (75% of sections), R (25% of sections) — in patterns, R means Thursday
Professors
Spring
- Damian Isla (100% of students) · reviews
Percentages are each professor's average share of the season's enrolled students in recent terms.
Links
Official catalog (CS course descriptions) · Student reviews on RateMyHusky · All CS courses · Plan it at numap.app