[PDF][PDF] Improving intrusion detection systems with multi-agent deep reinforcement learning: Enhanced centralized and decentralized approaches

A Bacha, F Barika Ktata, F Louati - Proceedings of the 20th …, 2023 - scitepress.org
Intrusion detection is a crucial task in the field of computer security as it helps protect these
systems against malicious attacks. New techniques have been developed to cope with the …

Reinforcement imitation learning for reliable and efficient autonomous navigation in complex environments

D Kumar - Neural Computing and Applications, 2024 - Springer
Reinforcement learning (RL) and imitation learning (IL) are quite two useful machine
learning techniques that were shown to be potential in enhancing navigation performance …

Advancing Investment Frontiers: Industry-grade Deep Reinforcement Learning for Portfolio Optimization

P Ndikum, S Ndikum - arXiv preprint arXiv:2403.07916, 2024 - arxiv.org
This research paper delves into the application of Deep Reinforcement Learning (DRL) in
asset-class agnostic portfolio optimization, integrating industry-grade methodologies with …

Multi-Defender Strategic Filtering Against Multi Agent Cyber Epidemics on Multi-Environment Model for Smart Grid Protection

K Bitirgen, ÜB Filik - E3S Web of Conferences, 2023 - e3s-conferences.org
The growing cyber space with the developments in cyber network technologies in smart grid
(SG) systems has necessitated questioning the reliability of networks and taking precautions …