Dasgupta, Pallab ; Chakrabarti, P. P. ; DeSarkar, S. C. (1996) Searching game trees under a partial order Artificial Intelligence, 82 (1-2). pp. 237-257. ISSN 0004-3702
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Official URL: http://linkinghub.elsevier.com/retrieve/pii/000437...
Related URL: http://dx.doi.org/10.1016/0004-3702(94)00085-9
Abstract
The problem of partial order game tree search arises from game playing situations where multiple, conflicting and non-commensurate criteria dictate the merit of a position of the game. In partial order game trees, the outcomes evaluated at the tip nodes are vectors, where each dimension of the vector represents a distinct criterion of merit. This leads to an interesting variant of the game tree searching problem where corresponding to every game playing strategy of a player, several outcomes are possible depending on the individual priorities of the opponent. In this paper, we identify the necessary and sufficient conditions for a set of outcomes to be inferior to another set of outcomes for every strategy. Using an algebra called Dominance Algebra on sets of outcomes, we describe a bottom-up approach to find the non-inferior sets of outcomes at the root node. We also identify shallow and deep pruning conditions for partial order game trees and present a partial order search algorithm on lines similar to the a-ß pruning algorithm for conventional game trees.
Item Type: | Article |
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Source: | Copyright of this article belongs to Elsevier Science. |
ID Code: | 5935 |
Deposited On: | 19 Oct 2010 10:08 |
Last Modified: | 16 May 2016 16:22 |
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