COMPSCI 570 – Artificial Intelligence Qualifying Exam

Exam is Closed Book

COMPSCI 570: Qualifying Exam Syllabus

Topics Covered for Algorithms and Representations for Artificial Intelligence:

- Search
- Uninformed search
- Informed search
- Constraint Satisfaction

- Game Playing
- Minimax
- alpha-beta search
- Introduction to game theory

- Logic and Knowledge Representation
- Propositional logic
- First order logic
- Theorem Proving

- Reasoning under uncertainty
- Probability
- Bayes nets
- Hidden Markov models and tracking

- Planning
- Classical planning
- Decision theory
- Stochastic planning (MDPs)

Prerequisites for COMPSCI 570 (provided for reference):

- Programming skills: You should be able to write and debug programs in C, C++, or Java without drama and without handholding
- Ability to do short proofs
- Facility with core computer science concepts:
- Computational complexity
- Analysis of algorithms

- Facility with mathematics concepts:
- Some calculus
- Basic Probability and statistics helpful but not required

Reference:

- Artificial Intelligence: A Modern Approach, Stuart Russell and Peter Norvig

Sample Exams: