Abstraction of Agents Executing Online and Their Abilities in the Situation Calculus
Abstract
We develop a general framework for abstracting online behavior of an agent that may acquire new knowledge during execution (e.g., by sensing), in the situation calculus and ConGolog. We assume that we have both a high-level action theory and a low-level one that represent the agent's behavior at different levels of detail. In this setting, we define ability to perform a task/achieve a goal, and then show that under some reasonable assumptions, if the agent has a strategy by which she is able to achieve a goal at the high level, then we can refine it into a low-level strategy to do so.
Cite
Text
Banihashemi et al. "Abstraction of Agents Executing Online and Their Abilities in the Situation Calculus." International Joint Conference on Artificial Intelligence, 2018. doi:10.24963/IJCAI.2018/235Markdown
[Banihashemi et al. "Abstraction of Agents Executing Online and Their Abilities in the Situation Calculus." International Joint Conference on Artificial Intelligence, 2018.](https://mlanthology.org/ijcai/2018/banihashemi2018ijcai-abstraction/) doi:10.24963/IJCAI.2018/235BibTeX
@inproceedings{banihashemi2018ijcai-abstraction,
title = {{Abstraction of Agents Executing Online and Their Abilities in the Situation Calculus}},
author = {Banihashemi, Bita and De Giacomo, Giuseppe and Lespérance, Yves},
booktitle = {International Joint Conference on Artificial Intelligence},
year = {2018},
pages = {1699-1706},
doi = {10.24963/IJCAI.2018/235},
url = {https://mlanthology.org/ijcai/2018/banihashemi2018ijcai-abstraction/}
}