Leveraging LLMs for Collaborative Human-AI Decision Making

Human-AI collaboration is a rapidly evolving field that seeks to leverage the complementary strengths of humans and artificial intelligence (AI) to solve complex problems. An area where such collaboration holds significant promise is in decision-making tasks, particularly in automated planning. As classical symbolic approaches are widely used in this field, they are limited when solving large and complex problems. Furthermore, they require expert knowledge in formal and structured languages to interact with, hindering their use. Recently, Large Language Models (LLMs) have emerged as a potential solution to these challenges but LLMs alone are not sufficient for solving such problems. However, a promising way to achieve seamless human-AI collaboration could be with hybrid approaches combining the strength of symbolic reasoning and the flexibility of LLMs.

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Publication Details

Journal
Proceedings of the AAAI Symposium Series
Published
2025-05-28
DOI
https://doi.org/10.1609/aaaiss.v5i1.35556
Citations
1
Primary Topic
Semantic Web and Ontologies
Type
article
Field-Weighted Citation Impact
2.48

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article

Leveraging LLMs for Collaborative Human-AI Decision Making

Anthony Favier, Pulkit Verma, Ngoc La, Julie A. Shah
1 citations
Proceedings of the AAAI Symposium Series
Semantic Web and Ontologies
2.48
article

Leveraging LLMs for Collaborative Human-AI Decision Making

Anthony Favier, Pulkit Verma, Ngoc La, Julie A. Shah
article en
1 citations

Abstract

Human-AI collaboration is a rapidly evolving field that seeks to leverage the complementary strengths of humans and artificial intelligence (AI) to solve complex problems. An area where such collaboration holds significant promise is in decision-making tasks, particularly in automated planning. As classical symbolic approaches are widely used in this field, they are limited when solving large and complex problems. Furthermore, they require expert knowledge in formal and structured languages to interact with, hindering their use. Recently, Large Language Models (LLMs) have emerged as a potential solution to these challenges but LLMs alone are not sufficient for solving such problems. However, a promising way to achieve seamless human-AI collaboration could be with hybrid approaches combining the strength of symbolic reasoning and the flexibility of LLMs.

Proceedings of the AAAI Symposium SeriesVol. 5(1)
Moscow Institute of Thermal Technology (RU)
Office of Naval Research
Openalex Percentile: Top 10%
Semantic Web and Ontologies
2.48
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