MURAL - Maynooth University Research Archive Library

    Accelerating Learning in multi-objective systems through Transfer Learning

    Taylor, Adam and Dusparic, Ivana and Galvan, Edgar and Clarke, Siobhan and Cahill, Vinny (2014) Accelerating Learning in multi-objective systems through Transfer Learning. 2014 International Joint Conference on Neural Networks (IJCNN). pp. 2298-2305. ISSN 2161-4407

    Download (1MB) | Preview

    Share your research

    Twitter Facebook LinkedIn GooglePlus Email more...

    Add this article to your Mendeley library


    Large-scale, multi-agent systems are too complex for optimal control strategies to be known at design time and as a result good strategies must be learned at runtime. Learning in such systems, particularly those with multiple objectives, takes a considerable amount of time because of the size of the environment and dependencies between goals. Transfer Learning (TL) has been shown to reduce learning time in single-agent, single-objective applications. It is the process of sharing knowledge between two learning tasks called the source and target. The source is required to have been completed prior to the target task. This work proposes extending TL to multi-agent, multi-objective applications. To achieve this, an on-line version of TL called Parallel Transfer Learning (PTL) is presented. The issues involved in extending this algorithm to a multi-objective form are discussed. The effectiveness of this approach is evaluated in a smart grid scenario. When using PTL in this scenario learning is significantly accelerated. PTL achieves comparable performance to the base line in one third of the time.

    Item Type: Article
    Keywords: Accelerating; Learning; multi-objective systems; Transfer Learning;
    Academic Unit: Faculty of Science and Engineering > Computer Science
    Faculty of Science and Engineering > Research Institutes > Hamilton Institute
    Item ID: 15361
    Identification Number:
    Depositing User: Edgar Galvan
    Date Deposited: 31 Jan 2022 14:24
    Journal or Publication Title: 2014 International Joint Conference on Neural Networks (IJCNN)
    Publisher: IEEE
    Refereed: Yes
    Use Licence: This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here

    Repository Staff Only(login required)

    View Item Item control page


    Downloads per month over past year

    Origin of downloads