Hill Climbing Algorithm in AI
| Institution | Jomo Kenyatta University of Science and Technology |
| Course | Information Technolo... |
| Year | 3rd Year |
| Semester | Unknown |
| Posted By | Jeff Odhiambo |
| File Type | |
| Pages | 6 Pages |
| File Size | 117.37 KB |
| Views | 2062 |
| Downloads | 0 |
| Price: |
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Description
Buy "Hill Climbing Algorithm in AI" now and learn how this powerful optimization technique can solve complex problems with ease. This comprehensive book delves into the intricacies of the hill climbing algorithm, a local search method that continuously moves towards higher elevations to find the optimal solution. Through detailed examples and practical applications, you'll explore how hill climbing is used to tackle mathematical challenges like the Traveling Salesman Problem. Perfect for both beginners and seasoned professionals, this book provides valuable insights into the algorithm's workings, its components, and various types, including simple, steepest-ascent, and stochastic hill climbing.
Discover the fascinating features of hill climbing, such as its greedy approach, generate and test variant, and state-space landscape. The book covers essential concepts like local and global maxima, plateaus, and ridges, and provides solutions to common problems encountered during the search process. By understanding these key elements, you'll be equipped to apply hill climbing algorithms to real-world scenarios and optimize your problem-solving strategies. "Hill Climbing Algorithm in AI" is an essential read for anyone looking to deepen their knowledge of AI's optimization techniques and enhance their analytical skills.
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