A Cognitively Inspired Approach for Knowledge Representation and Reasoning in Knowledge-Based Systems
Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence. Doctoral Consortium. Pages 4349-4349.
Abstract
In this thesis, I investigate a hybrid knowledge representation approach that combines classic knowledge representations, such as rules and ontologies, with other cognitively plausible representations, such as prototypes and exemplars. The resulting framework can combine the strengths of each approach of knowledge representation, avoiding their weaknesses. It can be used for developing knowledge-based systems that combine logic-based reasoning and similarity-based reasoning in problem-solving processes.
@inproceedings{ijcai2015p622,
title = {A Cognitively Inspired Approach for Knowledge Representation and Reasoning in Knowledge-Based Systems},
author = {Carbonera, Joel Luis and Abel, Mara},
booktitle = {Proceedings of the Twenty-Fourth International Joint Conference on
Artificial Intelligence, {IJCAI-15}},
publisher = {International Joint Conferences on Artificial Intelligence},
editor = {Qiang Yang and Michael Wooldridge},
pages = {4349--4349},
year = {2015},
month = {7},
note = {Doctoral Consortium},
url = {https://ijcai.org/proceedings/2015/622},
}
TY - CPAPER TI - A Cognitively Inspired Approach for Knowledge Representation and Reasoning in Knowledge-Based Systems AU - Carbonera, Joel Luis AU - Abel, Mara T2 - Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence, IJCAI-15 PB - International Joint Conferences on Artificial Intelligence PY - 2015 SP - 4349 EP - 4349 UR - https://ijcai.org/proceedings/2015/622 ER -Copied
Machine-readable versions of this paper, for tools and AI agents:
