Browsing by Subject "Replay memory"

Filter results by typing the first few letters
Now showing 1 - 1 of 1
  • Thumbnail Image
    ItemOpen Access
    Improving experience replay architecture with K-Means clustering
    (IEEE - Institute of Electrical and Electronics Engineers, 2023-08-28) Serbest, S.; Taşbaş, A. S.; Şahin, Safa Onur
    Replay memory highly affects the performance of deep reinforcement learning algorithms in terms of data efficiency and training time. How the experiences will be stored in the memory and sampling will be realized are subjects of ongoing research in the field. In this paper, a new replay memory module, called K-Means Replay Memory is designed. The module consists of two submodules called Recent Memory and Global Memory. New experiences are inserted only into recent memory and when the number of experiences in recent memory exceeds a certain limit, experience share occurs from recent memory to global memory. After the experience share, similarity sets are constituted via K-Means clustering algorithm within the stored experiences. While sampling, the distribution of experiences sampled from recent memory with respect to similarity sets and average losses obtained from neural networks are taken into account in order to compute set probabilities. Experiences are sampled from global memory by using these probabilities. Experiments are performed by using Prioritized Experience Replay, Uniform Experience Replay and K-Means Replay Memory, and obtained results are given in this paper.