[mod.ai] Seminar - Heuristic Search: Algorithms, Theory, and Learning

Betsy.Herk@A.CS.CMU.EDU (02/27/86)

Speaker:   Richard Korf, Asst. Prof., Comp. Sci. Dept., UCLA
Date:      Friday, March 14
Time:      1:00 - 2:30
Place:     5409 Wean Hall
Title:     Heuristic search:  Algorithms, theory, and learning
 
	   Abstract:
 
This talk will cover three new research results in the area of heuristic
search. The first is a new algorithm, called Iterative-Deepening-A*, that is
asymptotically optimal in terms of solution cost, time, and space among all
admissible heuristic tree searches. In practice, it is the only known
algorithm that is capable of finding optimal solutions to the Fifteen
Puzzle. The second is a theory which unifies the treatment of heuristic
evaluation functions in single-agent problems and two-person games. The
theory is based on the notion of a heuristic as a function that is invariant
over optimal solution paths. Based on this theory, we performed some
experiments on the automatic learning of heuristic functions.  Our program
was able to learn a set of relative weights for the different chess pieces
which is different from, but competitive with, the classical values.