Domain-Dependent and Domain-Independent Problem Solving Techniques
Abstract
Heuristic search is a general problem-solving method. Some heuristic search algorithms, like the well-known A* algorithm, are domain-independent, in the sense that their knowledge of the problem at-hand is limited to the (1) initial state, (2) state transition operators and their costs, (3) goal-test function, and (4) black-box heuristic function that estimates the value of a state. Prominent examples are A* and Weighted A*. Other heuristic search algorithms are domain-dependent, that is, customized to solve problems from a specific domain. A well-known example is conflict-directed A*, which is specifically designed to solve model-based diagnosis problems. In this paper, we review our recent advancements in both domain-independent and domain-dependent heuristic search, and outline several challenging open questions.
Cite
Text
Stern. "Domain-Dependent and Domain-Independent Problem Solving Techniques." International Joint Conference on Artificial Intelligence, 2019. doi:10.24963/IJCAI.2019/898Markdown
[Stern. "Domain-Dependent and Domain-Independent Problem Solving Techniques." International Joint Conference on Artificial Intelligence, 2019.](https://mlanthology.org/ijcai/2019/stern2019ijcai-domain/) doi:10.24963/IJCAI.2019/898BibTeX
@inproceedings{stern2019ijcai-domain,
title = {{Domain-Dependent and Domain-Independent Problem Solving Techniques}},
author = {Stern, Roni},
booktitle = {International Joint Conference on Artificial Intelligence},
year = {2019},
pages = {6411-6415},
doi = {10.24963/IJCAI.2019/898},
url = {https://mlanthology.org/ijcai/2019/stern2019ijcai-domain/}
}