Autors: Budakova, D. V.
Title: Reinforcement learning using for planning with compromises of a rescue operation
Keywords: Reinforcement learning, planning, compromises, rescue

Abstract: This article explores the creation of a library of plans, including the possibilities offered by the use of available specialized means and equipment in rescue operations. As a hazardous environment, a 3D model of an electrical substation is considered, and intelligent agent behavior is modeled with application in a serious game. The proposed modification of the Reinforcement Q-learning algorithm includes the introduction of matrices for the intensity of the characteristics of the considered disaster; safety thresholds; and new rules for choosing the next possible position in the evacuation path.

References

    Issue

    2023 11th International Scientific Conference on Computer Science, COMSCI 2023, 2023, Bulgaria,

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