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Means-Ends Analysis 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 | 4 Pages |
| File Size | 111.9 KB |
| Views | 1923 |
| Downloads | 0 |
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Description
Buy "Means-Ends Analysis in AI" now and learn how to solve complex and large problems with a mixture of forward and backward reasoning techniques. This comprehensive book introduces the concept of Means-Ends Analysis (MEA), a problem-solving strategy that limits search in AI programs by first solving major parts of a problem and then addressing smaller subproblems as they arise. With practical examples and detailed explanations, you'll explore how MEA works by evaluating differences between the current state and goal state, and applying operators to reduce these differences, making it accessible to both beginners and seasoned professionals.
Dive into the fascinating world of Operator Subgoaling, where operators are selected, and subgoals are set up to establish the preconditions for solving a problem. The book covers the essential algorithm for MEA and provides real-world examples to illustrate its application in various AI-driven tasks. "Means-Ends Analysis in AI" is an essential read for anyone looking to deepen their understanding of AI's problem-solving techniques and apply these methods to tackle real-world challenges effectively.
Below is the document preview.
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Introduction to Data structure
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Data Structures and Algorithm Analysis
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Data Structure: Stack.
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