Domain Engineering to Represent Human Behavior Using Multi-Agent Planning and Inductive Methodologies

Authors

  • Salena Torres Ashton School of Information, University of Arizona

DOI:

https://doi.org/10.1609/aaai.v38i21.30391

Keywords:

CMS: Social Cognition And Interaction, HAI: Human-Aware Planning And Behavior Prediction, KRR: Action Change And Causality, NLP: Discourse Pragmatics And Argument Mining, PRS: Activity And Plan Recognition

Abstract

This research combines multi agent planning, the psycholinguistics of question asking, procedural grounded theory, and hierarchical task networks to represent domains for automated planning.
AAAI-24 / IAAI-24 / EAAI-24 Proceedings Cover

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Published

2024-03-24

How to Cite

Ashton, S. T. (2024). Domain Engineering to Represent Human Behavior Using Multi-Agent Planning and Inductive Methodologies. Proceedings of the AAAI Conference on Artificial Intelligence, 38(21), 23381-23382. https://doi.org/10.1609/aaai.v38i21.30391

Issue

Vol. 38 No. 21: IAAI-24, EAAI-24, AAAI-24 Student Abstracts, Undergraduate Consortium and Demonstrations

Section

AAAI Doctoral Consortium Track