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.
Authors
- Anthony Favier
- Pulkit Verma
- Ngoc La
- Julie A. Shah
Institutions
- Moscow Institute of Thermal Technology (RU)
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
Funders
- Office of Naval Research