Save Big on Coursera Plus. 7,000+ courses at $160 off. Limited Time Only! Grab it Explore problem-solving and search techniques in artificial intelligence through this comprehensive lecture. Dive into problem-solving agents, goal formulation, and problem definition before examining various search strategies including breadth-first, uniform cost, depth-first, depth-limited, and iterative deepening depth-first search. Learn about search trees, the fringe (open list), and how to avoid repeated states using a closed list. Gain insights into performance considerations and understand the differences between tree search and graph search algorithms. Conclude with practical applications through assignment algorithm pseudocode.