Minimax Search Enhancements in Artificial Intelligence - Lecture 11

Explore advanced techniques for enhancing minimax search algorithms in this comprehensive lecture on artificial intelligence. Delve into crucial concepts such as actions and moves, state evaluation, and various types of enhancements. Learn about incremental progress, tie-breaking scores, and the state depth parity effect. Discover strategies for avoiding state copies and implementing effective move ordering. Investigate search extensions and bit operations, including bit sets and the XOR operator. Examine the use of bit boards for efficient game state representation. Finally, gain insights into transposition tables and Zobrist hashing for improved search performance. This lecture, part of a graduate-level AI course, provides essential knowledge for developing sophisticated game-playing algorithms.

- Intro
- Lecture Start
- Useful Links
- Actions / Moves
- State Evaluation
- Types of Enhancements
- Incremental Progress
- Tie-Breaking Scores
- State Depth Parity Effect
- Avoiding State Copies
- Move Ordering
- Search Extensions
- Bit Operations
- Bit Sets
- XOR Operator
- Bit Boards
- Transposition Tables
- Zobrist Hashing