Uncertainty in Artificial Intelligence
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A Heuristic Search Algorithm for Solving First-Order MDPs
Eldar Karabaev, Olga Skvortsova
We present a heuristic search algorithm for solving first-order MDPs (FOMDPs). Our approach combines first-order state abstraction that avoids evaluating states individually, and heuristic search that avoids evaluating all states. Firstly, we apply state abstraction directly on the FOMDP avoiding propositionalization. Such kind of abstraction is referred to as firstorder state abstraction. Secondly, guided by an admissible heuristic, the search is restricted only to those states that are reachable from the initial state. We demonstrate the usefullness of the above techniques for solving FOMDPs on a system, referred to as FCPlanner, that entered the probabilistic track of the International Planning Competition (IPC'2004).
Pages: 292-299
PS Link:
PDF Link: /papers/05/p292-karabaev.pdf
AUTHOR = "Eldar Karabaev and Olga Skvortsova",
TITLE = "A Heuristic Search Algorithm for Solving First-Order MDPs",
BOOKTITLE = "Proceedings of the Twenty-First Conference Annual Conference on Uncertainty in Artificial Intelligence (UAI-05)",
ADDRESS = "Arlington, Virginia",
YEAR = "2005",
PAGES = "292--299"

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