AAAI 2026technical0 citations
Strategic Tool Enhanced AI Agent for Multi-Issue Negotiation (Student Abstract)
Daiki Kitashima, Ryota Higa, Katsuhide Fujita
Abstract
Automated negotiation, a form of interaction among autonomous agents, plays a central role in multi-agent systems, yet the application of large language model (LLM) in this domain remains underexplored. An LLM can serve as a meta-strategist, adaptively selecting explicit strategies for execution by external strategic tools based on its capabilities. We propose a negotiation AI agent equipped with explicit strategic tools, including time-dependent and tit-for-tat negotiation strategies. Our results show that strategic tool enhanced negotiators achieve approximately 16% higher average utility compared with baseline, latest LLM negotiators.
BibTeX
@inproceedings{aaai2026_strategictoolenh,
title = {Strategic Tool Enhanced AI Agent for Multi-Issue Negotiation (Student Abstract)},
author = {Daiki Kitashima and Ryota Higa and Katsuhide Fujita},
booktitle = {AAAI 2026},
year = {2026}
}