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| Title: | A New Pruning Method for Solving Decision Trees and Game Trees |
| Authors: | Shenoy, Prakash P. |
| Keywords: | Decision trees
Game Trees
Roll-back method
Scenario trees |
| Issue Date: | Aug-1995 |
| Publisher: | Morgan Kaufmann Publishers |
| Extent: | 145991 bytes |
| Type: | Book chapter |
| Citation: | Shenoy, P. P., "A New Pruning Method for Solving Decision Trees and Game Trees," in P. Besnard and S. Hanks (eds.), Uncertainty in Artificial Intelligence, Vol. 11, 1995, pp. 482--490, Morgan Kaufmann, San Francisco, CA. |
| Abstract: | The main goal of this paper is to describe a newpruning method for solving decision trees and game trees. The pruning method for decision trees suggests a slight variant of decision trees that we call scenario trees. In scenario trees, we do not need a conditional probability for each edge emanating from a chance node. Instead, we require a joint probability for each path from the root node to a leaf node. We compare the pruning method to the traditional rollback method for decision trees and game trees. For problems that require Bayesian revision of probabilities, a scenario tree representation with the pruning method is more efficient than a decision tree representation with the rollback method. For game trees, the pruning method is more efficient than the rollback method. |
| URI: | http://hdl.handle.net/1808/179 |
| ISBN: | 1-55860-385-9 |
| Appears in Collections: | School of Business Articles
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