Abstract

The growing prominence of LLMs has led to an increase in the development of AI tutoring systems. These systems are crucial in providing underrepresented populations with improved access to valuable education. One important area of education that is unavailable to many learners is strategic bargaining related to negotiation. To address this, we develop a LLM-based Assistant for Coaching nEgotiation (ACE). ACE not only serves as a negotiation partner for users but also provides them with targeted feedback for improvement. To build our system, we collect a dataset of negotiation transcripts between MBA students. These transcripts come from trained negotiators and emulate realistic bargaining scenarios. We use the dataset, along with expert consultations, to design an annotation scheme for detecting negotiation mistakes. ACE employs this scheme to identify mistakes and provide targeted feedback to users. To test the effectiveness of ACE-generated feedback, we conducted a user experiment with two consecutive trials of negotiation and found that it improves negotiation performances significantly compared to a system that doesn’t provide feedback and one which uses an alternative method of providing feedback. Comments: EMNLP 2024 Subjects: Computation and Language (cs.CL); Human-Computer Interaction (cs.HC) Cite as: arXiv:2410.01555 [cs.CL] (or arXiv:2410.01555v1 [cs.CL] for this version)

https://doi.org/10.48550/arXiv.2410.01555 Focus to learn more

LLM agent for coaching negotiation

This paper is about a LLM-based negotiation coaching system. The system is designed to provide feedback to users on their negotiation performance. The system is trained on a dataset of negotiation transcripts between MBA students. The dataset is annotated with negotiation mistakes. The system uses this annotation to identify mistakes and provide targeted feedback to users. The system is evaluated in a user experiment and found to improve negotiation performance significantly compared to a system that doesn’t provide feedback and one which uses an alternative method of providing feedback.

The feedback is made during the negotiation process. The system provides feedback

  • after each turn
  • after each negotiation

They made 8 negotiation mistakes:

  • Strategic walk-away point (preparation error)
  • Strategic target price (preparation error)
  • Breaking the ice (negotiatoin error)
  • Giving the first offer (negotiation error)
  • Ambitious opening point (negotiation error)
  • Strong counteroffer (negotiation error)
  • Including rationale (negotiation error)
  • Strategic closing behavior (negotiation error)