Autors: Budakova, D. V., V. S. Petrova-Dimitrova., L. G. Dakovski.
Title: Smart Broker Agent Learning How to Reach Appropriate Goal by Making Appropriate Compromises
Keywords: Intelligent System, Reinforcement Learning, Intelligent Virtual Agents, Smart Broker Learning Agent

Abstract: In this paper a new Smart Broker Learning Agent (SBLA) has been proposed, which trains to find the most acceptable solution to a given problem, according to the individual requirements and emotions of a particular user. For this purpose, a new structure of the agent has been proposed and reinforcement-learning algorithm has been used. When the scenarios and criteria under consideration are complex, and when mixed emotions arise, it may be necessary to compromise on certain criteria in order to achieve the goal. Then knowledge of the preferences and emotions of the particular user is needed. In these cases, the SBLA does not allow compromises that are unacceptable to this user. The structure and the way of acting of the agent have been considered. The knowledge that the SBLA must have and the process of its formation have been described. The scenarios for solving a specific task and the conducted experiments have been presented. Some contributions have been discussed.

References

    Issue

    ICAART 2021, vol. Volume 1, pp. 181-188, 2021, Portugal, ISBN 978-989-758-484-8

    Full text of the publication

    Вид: публикация в международен форум, публикация в реферирано издание, индексирана в Scopus