A branch of artificial intelligence concerned with generating multi-part solutions to problems. Examples include game-playing AI, industrial automation, turn-by-turn directions
Automated planning and scheduling is the sub-field of artificial intelligence concerned with generating multi-part solutions to problems.
Some familiar examples of planning algorithms and systems include:
- The "Minimax" algorithm for choosing the best move in a two-player game (such as Tic-Tac-Toe, or Chess)
- The "A*" algorithm for heuristic search
- GPS navigation software, providing turn-by-turn driving directions
- Unmanned aerial vehicles ("drones") perform automatic corrections to stay on course despite changes in wind or other disruptions
Commonly used University textbooks on the subject:
- Russell, Stuart J.; Norvig, Peter (2003), Artificial Intelligence: A Modern Approach (2nd ed.), Upper Saddle River, New Jersey: Prentice Hall, pp. 375–459, ISBN 0-13-790395-2
- Ghallab, Malik; Nau, Dana S.; Traverso, Paolo (2004), Automated Planning: Theory and Practice, Morgan Kaufmann, ISBN 1-55860-856-7
