1. 2004: Topics Covered in COSC 6368
More general topics:
heuristic search and search algorithm in general
logical reasoning
probabilistic reasoning
AI-specific Topics:
resolution / theorem proving
reasoning in uncertain environments: naïve Bayesian systems and belief networks
machine learning centering on neural networks, decision trees and reinforcement learning
brief coverage of soft computing, evolutionary computing, data mining, philosophical aspects of AI
The 2004 class was taught more “applied” and project/homework oriented  more time was allocated in lectures to discuss projects and homework problems (less coverage of other AI topics)

2. AI in General and What Was not Covered in COSC 6368
Robotics is a quite important sub-field of AI, but very few teach it in the graduate AI class.
Planning deserves more coverage.
Intelligent Agents and AI for the Internet might become more important changing what is taught in graduate AI-classes in a few years from now.
Data Mining should perhaps be covered in more depth, considering research projects in our department, but having a separate class covering data mining seems to be a better idea.
Knowledge-based systems deserve more coverage.