Keywords
AI; Negotiation; LLM; Prompt Engineering; Fine-Tuning; Machine Learning
Abstract
Negotiation is a complex field that can benefit from introducing artificial intelligence (AI); doing so would benefit researchers as they try to deepen their understanding of human-human and human-agent negotiation. Investigating how large language models (LLMs) can generate negotiation dialogue with emotional context would bring agents closer to acting more human. This study explores how fine-tuning and prompt engineering can achieve this goal and the possibilities for an AI that fills these criteria to be included in the Interactive Arbitration Guide Online platform (IAGO). Doing so will make the negotiation interactions in IAGO feel more complex and natural, allowing researchers to further their understanding of negotiation conversations and concepts.
Thesis Completion Year
2025
Thesis Completion Semester
Spring
Thesis Chair
Mell, Johnathan
College
College of Engineering and Computer Science
Department
Computer Science
Thesis Discipline
Computer Science
Language
English
Access Status
Open Access
Length of Campus Access
None
Campus Location
Orlando (Main) Campus
STARS Citation
Weener, Kylee R., "Generating Negotiations for IAGO" (2025). Honors Undergraduate Theses. 327.
https://stars.library.ucf.edu/hut2024/327
Rights Statement
