Constraint Satisfaction: Formulation and Algorithms

This lecture covers the formulation of constraint satisfaction problems (CSP) and systematic algorithms for solving them. It discusses the challenges of combinatorial explosion in general search algorithms and introduces the concept of constraint satisfaction to enable more efficient methods. Examples such as resource allocation problems are used to illustrate the formulation of CSP. The lecture also explores systematic algorithms like depth-first search and heuristics like backjumping and forward checking. Various techniques for improving the efficiency of CSP solutions, such as local search algorithms like hill-climbing and simulated annealing, are presented. The importance of consistency algorithms in reducing search complexity is highlighted, along with practical applications in scheduling, planning, and design problems.