AI03 Problem-Solving Agents: AI Search Strategies
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AI03 Problem-Solving Agents: AI Search Strategies
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The provided texts comprehensively outline problem-solving agents and search algorithms in Artificial Intelligence. They explain how these agents formulate problems by defining states, initial states, goal states, actions, and action costs to create an abstract model of the environment. The sources detail various uninformed search strategies like Breadth-First Search, Uniform-Cost Search, Depth-First Search, Iterative Deepening Search, and Bidirectional Search, evaluating them based on completeness, optimal cost, time complexity, and space complexity. Furthermore, the texts explore informed (heuristic) search strategies such as Greedy Best-First Search and A* Search, emphasizing the critical role of heuristic functions derived through methods like problem relaxation, pattern databases, and landmark points, or even learned using machine learning.