Richard Korf

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Richard Korf [1] Richard Earl Korf,

an American computer scientist and professor at the University of California, Los Angeles. He received his B.S. from MIT in 1977, and his M.S. and Ph.D. from Carnegie Mellon University in 1980 and 1983. His research is in the areas of problem-solving, heuristic search, and planning in artificial intelligence [2]. In particular, Richard Korf researched and published on best-first versus depth-first‎ search algorithms, and emphasized depth-first iterative deepening, as in IDA* versus A*.

Richard Korf (1984). The Complexity of Brute Force Search. Technical Report, Department of Computer Science, Columbia University [6] [7]
Richard Korf (1985). Depth-first Iterative-Deepening: An Optimal Admissible Tree Search. pdf
Richard Korf (1985). Learning to solve problems by searching for macro-operators. Pitman.
Richard Korf (1985). Macro-operators: A weak method for learning. Artificial Intelligence, Vol. 26, No. 1
Jens Christensen, Richard Korf (1986). A Unified Theory of Heuristic Evaluation functions and Its Applications to Learning. AAAI-86, pdf.
Richard Korf (1987). Planning as Search: A Quantitative Approach. Artificial Intelligence, Vol. 33, pp. 65-88.
Bruce Abramson, Richard Korf (1987). A Model of Two-Player Evaluation Functions. AAAI-87. pdf
Chris Ferguson, Richard Korf (1988). Distributed Tree Search and its Application to Alpha-Beta Pruning. AAAI-88, pdf

Nageshwara Rao Vempaty, Vipin Kumar, Richard Korf (1991). Depth-First vs Best-First Search. AAAI-91, pdf
Richard Korf (1993). Linear-Space Best-First Search. Artificial Intelligence, Vol. 62, No. 1, pdf
Richard Korf, Max Chickering (1993). Best-first Minimax Search: First Results. AAAI-93, pdf
Weixiong Zhang, Richard Korf (1993). Depth-first vs. best-first search: New results. AAAI-93
Richard Korf, Max Chickering (1994). Best-first minimax search: Othello results. AAAI-94, pdf
Richard Korf, Max Chickering (1996). Best-first minimax search. Artificial Intelligence, Vol. 84, No 1-2
Richard Korf (1997). Finding Optimal Solutions to Rubik’s Cube Using Pattern Databases. AAAI-97, pdf
Richard Korf (1997). Does Deep Blue use AI? AAAI-97, Workshop on Deep Blue vs. Kasparov : The Significance for Artificial Intelligence, pdf
Richard Korf (1997). Does DEEP BLUE use Artificial Intelligence? ICCA Journal, Vol. 20, No. 4 [8]
Stefan Edelkamp, Richard Korf (1998). The Branching Factor of Regular Search Spaces. AAAI-98, pdf
Richard Korf, Michael Reid (1998). Complexity Analysis of Admissible Heuristic Search. AAAI-98, pdf

Richard Korf (2000). Finding Optimal Solution to Rubik’s Cube Using Pattern Databases. Games in AI Research (eds. Jaap van den Herik and Hiroyuki Iida), Universiteit Maastricht
Nathan Sturtevant, Richard Korf (2000). On Pruning Techniques for Multi-Player Games. AAAI-2000, pdf
Richard Korf, Michael Reid, Stefan Edelkamp (2001). Time complexity of iterative-deepening-A*. Artificial Intelligence, Vol. 129, No. 1-2
Richard Korf, Ariel Felner (2002). Disjoint Pattern Database Heuristics. in “Chips Challenging Champions: Games, Computers and Artificial Intelligence”, edited by Jonathan Schaeffer and Jaap van den Herik. Elsevier Science
Ariel Felner, Richard Korf, Ram Meshulam, Robert Holte (2007). Compressed Pattern Databases. JAIR, Vol. 30, pdf
Richard Korf, Ariel Felner (2007). Recent Progress in Heuristic Search: A Case Study of the Four-Peg Towers of Hanoi Problem. IJCAI-07
Richard Korf (2008). Minimizing Disk I/O in Two-Bit Breadth-First Search. AAAI-2008, pdf

Joseph K. Barker, Richard Korf (2011). Solving 4x5 Dots-And-Boxes. AAAI-2011, pdf
Joseph K. Barker, Richard Korf (2012). Solving Peg Solitaire with Bidirectional BFIDA. AAAI-2012
Joseph K. Barker, Richard Korf (2012). Solving Dots-And-Boxes. AAAI-2012
Richard Korf (2012). Research Challenges in Combinatorial Search. AAAI-2012
Richard Korf (2014). How Do You Know Your Search Algorithm and Code Are Correct? SOCS 2014, pdf
Richard Korf (2016). Comparing Search Algorithms Using Sorting and Hashing on Disk and in Memory. IJCAI 2016, pdf

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