A proposal of automatic negotiation simulator Jupiter for negotiation agent using machine learning.

Abstract

The purpose of this paper is to propose Jupiter, a new environment for automated negotiations in which we can easily create agents that is able to use machine learning. Genius is cited as a prior study of the environment where automated negotiation can be simulated. It provides an environment for automated negotiations that aim to solve multi-issue negotiation problems. In the field of automated negotiation, it is expected that agreement results are optimized by machine learning. However, it is difficult to use Genius to simulate automated negotiations with agents using machine learning, because the past negotiations information provided by Genius is insufficient. As above, we propose Jupiter as a new automated negotiation environment in which we can easily create agents that is able to use machine learning. In addition, we compare Jupiter with Genius and show the superiority of Jupiter.