Problem solving and Search

The ability to solve problems is fundamental to achieving true intelligence in an artificial system, and it forms a critical early pillar of AI research. This capacity is primarily implemented through search strategies, which define the methodology an agent uses to navigate a potential solution space—often represented as a graph of states—to reach a desired goal state. These techniques range from simple, uninformed methods like Breadth-First Search and Depth-First Search, which systematically explore the space, to more sophisticated, informed heuristic search algorithms such as A* ($ ext{A}^*$) and Greedy Best-First Search. The primary challenge lies in selecting a strategy that ensures completeness (finding a solution if one exists) and optimality (finding the best solution) while minimizing the computational cost in terms of time and memory.