reinforcement learning

Beyond static snapshots: gated recurrent units and graph attention networks for smarter multi-agent traffic control

Existing multi-agent reinforcement learning (MARL) approaches for traffic signal control often fail to capture two critical characteristics of real-world urban traffic: the dynamic spatio-temporal propagation of congestion across intersections and the frequent imperfection of sensor data. To address these fundamental g...

Review of: "Enhancing Code LLMs with Reinforcement Learning in Code Generation: A Survey"

Error-driven representation learning in the mesolimbic system

In reinforcement learning, an agent learns to map representations of the environment state to predictions of future reward. Most prior work in neuroscience has assumed a fixed representation and studied how reward prediction errors (thought to be conveyed by phasic dopamine signals) are used to update the mapping from...

Hybrid Attention Vision Transformer Framework for Cost Efficient Cloud Resource Allocation and Load Balancing

This paper aims to develop FairViT-ShrikeNet , which is a hybrid system that combines attention motivated deep reinforcement learning, Vision Transformer workload encoding, and Shrike metaheuristic optimization to realise fairness sensitive and cost effective resource allocation in cloud computing systems. The approach...

X-MAQRL: Explainability-Driven Mobility and Attack-Aware Q-Learning Routing for Flying Ad Hoc Networks

Barrier-Function-Constrained Residual RL-Based Current Control for LCL-Filtered NPC Inverters under Weak-Grid Operation

As renewable energy penetration continues to grow, grid-connected inverters are increasingly required to operate reliably under weak-grid conditions, where low short-circuit ratios, changing grid impedances, and rapid disturbances reveal the limitations of conventional fixed-gain PI current controllers. Reinforcement l...

Secure and scalable IoT device management with blockchain, K-anonymity, and deep reinforcement learning

The vast expansion of Internet of Things (IoT) ecosystems has posed significant challenges regarding security, scalability, latency, and user privacy, which are not properly handled by the conventional architectures. To solve these issues, the authors of this paper suggest an integrated IoT management framework that em...

Reinforcement Learning for Intensity Control: An Application to Choice-Based Network Revenue Management

Learning from Snapshots Is Not Enough: An Even-Driven Continuous-Time Reinforcement Learning Framework Revenue management systems evolve continuously, but reinforcement learning often requires dividing time into a fixed grid. Fine grids improve accuracy but increase computation; coarse grids can sacrifice performance....

Steady-blowing jet control of a finite-length square cylinder at high reynolds number: Turbulence characteristics and DRL-based adaptive drag reduction

This study systematically investigates the turbulence characteristics and drag-reduction mechanisms of steady wall-normal blowing control on a three-dimensional square cylinder at Re = 22000 using a large-eddy simulation (LES) with the Smagorinsky subgrid-scale model. Four jet positions at the cylinder corners—the wind...

RL-accelerated OSQP for real-time asymmetric corotational beam contact simulation in continuum robots

The real-time simulation of highly deformable slender structures interacting with complex, irregular boundaries remains a computationally demanding challenge in computational mechanics. A prominent motivating application for this fundamental problem is the navigation of continuum surgical robots within narrow anatomica...

Kemahiran berfikir aras tinggi dalam buku teks Pendidikan Moral Tahun Lima Sekolah Jenis Kebangsaan Tamil [Higher order thinking skliis in the Moral Education text book for year five Tamil National Type Schools]

Malaysia's low ranking in TIMSS and PISA exposes students' weaknesses in mastering Higher Order Thinking Skills (KBAT) due to a curriculum that overemphasizes rote learning. This scenario contributes to disciplinary issues and moral conflicts among Tamil Vernacular Primary School (SJKT) students because of their inabil...

Application of the W-shaped process for a Reinforcement Learning use case on drone navigation

The interest in Machine Learning (ML) has spread to safety systems due to its ability to solve tasks that cannot be explicitly programmed, including pattern recognition, object detection, and autonomous control. To ensure the safe integration of ML in avionics, the European Union Aviation Safety Agency (EASA) proposed...