Problem Formulation and Automated Problem Solving

Catalog description

This course introduces students to methods for automated problem solving requiring intelligence by formulating and solving problems as search, optimization, or constraint satisfaction problems. Topics of the course include but are not limited to: Problem-solving as state space search, Basic search algorithms and their properties, Finding optimal solutions (Best first search, A* Search, Heuristic search); Problem Solving through Problem Reduction, Search in non-deterministic environments, Problem solving in partially observable environments, Problem solving as Constraint Satisfaction, and Adversarial problem solving (optimal decisions in games; minimax search; etc.). Laboratory assignments will be used to provide students with hands-on experience in implementing and experimenting with AI problem solving methods. Upon successful completion of the course, students will be able to formulate and solve real-world problems of moderate complexity using modern search algorithms.