Tootfinder

Beyond ReLU: Chebyshev-DQN for Enhanced Deep Q-Networks
Saman Yazdannik, Morteza Tayefi, Shamim Sanisales
https://arxiv.org/abs/2508.14536 https://arxiv.or…

Beyond ReLU: Chebyshev-DQN for Enhanced Deep Q-Networks
The performance of Deep Q-Networks (DQN) is critically dependent on the ability of its underlying neural network to accurately approximate the action-value function. Standard function approximators, such as multi-layer perceptrons, may struggle to efficiently represent the complex value landscapes inherent in many reinforcement learning problems. This paper introduces a novel architecture, the Chebyshev-DQN (Ch-DQN), which integrates a Chebyshev polynomial basis into the DQN framework to create…

A Deep Q-Network based power control mechanism to Minimize RLF driven Handover Failure in 5G Network
Kotha Kartheek, Shankar K. Ghosh, Megha Iyengar, Vinod Sharma, Souvik Deb
https://arxiv.org/abs/2510.05762

A Deep Q-Network based power control mechanism to Minimize RLF driven Handover Failure in 5G Network
The impact of Radio link failure (RLF) has been largely ignored in designing handover algorithms, although RLF is a major contributor towards causing handover failure (HF). RLF can cause HF if it is detected during an ongoing handover. The objective of this work is to propose an efficient power control mechanism based on Deep Q-Network (DQN), considering handover parameters (i.e., time-to-preparation, time-to-execute, preparation offset, execution offset) and radio link monitoring parameters (T…

HCQA: Hybrid Classical-Quantum Agent for Generating Optimal Quantum Sensor Circuits
Ahmad Alomari, Sathish A. P. Kumar
https://arxiv.org/abs/2508.21246 https://

HCQA: Hybrid Classical-Quantum Agent for Generating Optimal Quantum Sensor Circuits
This study proposes an HCQA for designing optimal Quantum Sensor Circuits (QSCs) to address complex quantum physics problems. The HCQA integrates computational intelligence techniques by leveraging a Deep Q-Network (DQN) for learning and policy optimization, enhanced by a quantum-based action selection mechanism based on the Q-values. A quantum circuit encodes the agent current state using Ry gates, and then creates a superposition of possible actions. Measurement of the circuit results in prob…