Overview
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Explore informed search algorithms and heuristic-based problem-solving techniques in this artificial intelligence lecture from Memorial University's Computer Science program. Delve into the fundamentals of heuristic search methods, starting with best-first search approaches and the critical role of heuristic functions in guiding search algorithms. Learn about greedy best-first search strategies and understand the importance of admissible heuristics in ensuring optimal solutions. Master the A* search algorithm, including its theoretical foundations, optimality guarantees, and performance characteristics. Examine the concept of consistent heuristics and their impact on algorithm efficiency. Follow a detailed illustrated example demonstrating A* search in action, then discover the weighted A* variant for balancing solution quality with computational speed. Conclude with practical demonstrations comparing different search algorithms and their relative performance in various scenarios. This comprehensive coverage provides essential knowledge for understanding how intelligent systems navigate complex problem spaces using informed search strategies.
Syllabus
- Intro
- Informed Heuristic Search
- Best-First Search BeFS
- Heuristic Function hn
- Greedy Best-First Search GBeFS
- Admissible Heuristic
- A* Search Algorithm
- Consistent Heuristic
- A* Search Optimality + Performance
- A* Search Illustrated Example
- Weighted A* Algorithm
- Demo + Algorithm Comparison
Taught by
Dave Churchill