CSC 342 Artificial Intelligence

This course will cover many topics and techniques in artificial intelligence. Topics include search, constraint satisfaction, knowledge representation, planning, logical and Bayesian reasoning, learning and game playing. Techniques include pattern matching, data-driven programming, propositional logic, first-order logic, substitution rules, heuristic search, transition networks, artificial neural networks, Bayesian decision networks and evolutionary computation. Additionally, students will analyze the computational complexities for all algorithms discussed. Co-requisite: CSC 302 or permission of instructor.