AI education matters

Author:

Sturtevant Nathan R.1

Affiliation:

1. University of Alberta

Abstract

In this column, we share advice and resources for teaching and learning about heuristic search algorithms. These are algorithms like A* (Hart, Nilsson, & Raphael, 1968), IDA* (Korf, 1985) and others that use admissible heuristics to find optimal and suboptimal solutions to shortest path problems.

Publisher

Association for Computing Machinery (ACM)

Reference15 articles.

1. Culberson J. C. & Schaeffer J. (1996). Searching with pattern databases. Advances in Artificial Intelligence 402--416. Culberson J. C. & Schaeffer J. (1996). Searching with pattern databases. Advances in Artificial Intelligence 402--416.

2. Edelkamp S. & Schrödl S. (2012). Heuristic search - theory and applications. Academic Press. Retrieved from http://www.elsevierdirect.com/product.jsp?isbn=9780123725127 Edelkamp S. & Schrödl S. (2012). Heuristic search - theory and applications. Academic Press. Retrieved from http://www.elsevierdirect.com/product.jsp?isbn=9780123725127

3. Felner A. Stern R. Shimony S. E. Boyarski E. Goldenberg M. Sharon G. ... Surynek P. (2017). Search-based optimal solvers for the multi-agent pathfinding problem: Summary and challenges.. Felner A. Stern R. Shimony S. E. Boyarski E. Goldenberg M. Sharon G. ... Surynek P. (2017). Search-based optimal solvers for the multi-agent pathfinding problem: Summary and challenges..

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