Richard Korf

Richard Korf is a Professor Emeritus of computer science at the University of California, Los Angeles. He received his B.S. from M.I.T. in 1977, and his M.S. and Ph.D. from Carnegie-Mellon University in 1980 and 1983, respectively, all in computer science. From 1983 to 1985, he served as Herbert M. Singer Assistant Professor of Computer Science at Columbia University. His research is in the areas of problem-solving, heuristic search, and planning in artificial intelligence. He is the author of "Learning to Solve Problems by Searching for Macro-Operators" (Pitman, 1985).

Richard E. Korf is a Professor Emeritus of Computer Science at the University of California, Los Angeles, known for his work in heuristic search. His research focuses on developing efficient algorithms for solving complex problems, particularly in the areas of optimal search and planning. Korf has made significant contributions to heuristic search techniques, including iterative-deepening, real-time search, and pattern databases. His work on optimal solutions for problems like Rubik's Cube and number partitioning highlights his expertise in algorithm design and optimization. Additionally, he has explored cooperative pathfinding and limited discrepancy search, emphasizing the importance of efficiency and completeness in search algorithms.