Tag: edge AI

State-Space Search: Algorithms, Complexity, Extensions, and Applications by Weix

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State-space search is a fundamental problem-solving technique used in artificial intelligence and computer science to find a sequence of actions that lead from an initial state to a goal state. In his book “State-Space Search: Algorithms, Complexity, Extensions, and Applications,” author Weix explores the various algorithms, complexities, extensions, and applications of state-space search.

From simple uninformed search algorithms like breadth-first search and depth-first search to more advanced informed search algorithms like A*, Weix covers a wide range of techniques used to efficiently explore state spaces. He also delves into the complexities of state-space search, discussing how factors like branching factor, depth of the search tree, and heuristic information can impact the efficiency of search algorithms.

In addition to traditional state-space search algorithms, Weix also explores extensions and variations of the basic search framework, such as bidirectional search, iterative deepening search, and constraint satisfaction problems. He discusses how these extensions can improve the performance of search algorithms in different problem domains.

Finally, Weix examines the practical applications of state-space search in various fields, including robotics, planning, game playing, and natural language processing. By showcasing real-world examples of state-space search in action, he highlights the importance and versatility of this problem-solving technique.

Overall, “State-Space Search: Algorithms, Complexity, Extensions, and Applications” is a comprehensive guide to state-space search that is essential reading for students, researchers, and practitioners in the field of artificial intelligence and computer science.
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