Abstract:  Effective strategies for dealing with patent licensing have been attracting greatermore interests amongst enterprises due to acceleration ined high- technologies development and rapidly expanding international trades. In a modern society, patent licensing is a widely accepted approach, viewed as a form of a formal transaction. It allows for, for allowing a licensee to implement the patented technology for future applications, and in return, paying royalties to a licensor for the potential value of the patentsed provided. Until recently,p to nowadays, most patent licensing activities wereare face-to-face talks, however, due to complexities and uncertainty during the negotiation processes of a patent licensing transaction, asymmetric information between licensors and licensees largely exists. This can and hinders a fare and optimal solution for licensing transactions. This study attempts to design a multi-agent negotiation system that employs Genetic Algorithms (GA) for automatically choosing best-fit strategies for patent licensing matching. The system, which serves as a patent intermediary, relies on experts from industries and professional organizations to establish the licensing negotiation conditions. Based on these realistic conditions providedinput by experts, this automated negotiation system is able to conduct preliminary negotiation activities between licensees and licensors. Through the automated process, lower costs and higher efficiency can be achieved.. We hope that thisthe system has the potential for handling multi-attribute based negotiations forin real situations in the future.

Keywords: Patent licensing; Multi-agent; Negotiation; Genetic Algorithm (GA); Support system