A Heuristic Search Algorithm for Solving First-Order MDPs
Abstract
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 first-order 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 FC-Planner, that entered the probabilistic track of the International Planning Competition (IPC'2004).
Cite
Text
Karabaev and Skvortsova. "A Heuristic Search Algorithm for Solving First-Order MDPs." Conference on Uncertainty in Artificial Intelligence, 2005.Markdown
[Karabaev and Skvortsova. "A Heuristic Search Algorithm for Solving First-Order MDPs." Conference on Uncertainty in Artificial Intelligence, 2005.](https://mlanthology.org/uai/2005/karabaev2005uai-heuristic/)BibTeX
@inproceedings{karabaev2005uai-heuristic,
title = {{A Heuristic Search Algorithm for Solving First-Order MDPs}},
author = {Karabaev, Eldar and Skvortsova, Olga},
booktitle = {Conference on Uncertainty in Artificial Intelligence},
year = {2005},
pages = {292-299},
url = {https://mlanthology.org/uai/2005/karabaev2005uai-heuristic/}
}