Studying cooperative multi-agent reinforcement learning in networks حسب Oudah, Mayada Mohamed

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Multi-Agent Learning of Strategies in Abstract Argumentation Mechanisms حسب Nemer, Rama

"…The importance of this kind of work lies in the fact that it combines two aspects of multi-agent systems that have been quite separate to-date: argumentation protocols and multi-agent learning in games.…"
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Multi Agent Reinforcement Learning Approach for Autonomous Fleet Management حسب Alhusin, Mohammed Omer Alamin

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Single channel speech denoising by DDPG reinforcement learning agent حسب Sania Gul (18272227)

"…In this paper, a novel SD algorithm is presented based on the deep deterministic policy gradient (DDPG) agent; an off-policy reinforcement learning (RL) agent with a continuous action space. …"

Experimental evaluation of multi-agent reinforcement learning in real-world scale-free networks حسب Al Hashimi, Rashid

"…However, the study and analysis of the state-of-the-art multi-agent reinforcement learning (MARL) algorithms have been limited to small problems involving few number of learning agents.The purpose of this project is to conduct an extensive evaluation and comparison of MARL algorithms when used in networks that exhibit the scale-free property. …"
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Multi-Agent Meta Reinforcement Learning for Reliable and Low-Latency Distributed Inference in Resource-Constrained UAV Swarms حسب Marwan Dhuheir (19170898)

"…Given the complexity of the LDTP solution for managing online requests, we propose a real-time, lightweight solution using multi-agent meta-reinforcement learning. Our approach is tested on CNN networks and benchmarked against state-of-the-art conventional reinforcement learning algorithms. …"

Public health utility of cause of death data: applying empirical algorithms to improve data quality حسب Sarah Charlotte Johnson (9715415)

A conjugate self-organizing migration (CSOM) and reconciliate multi-agent Markov learning (RMML) based cyborg intelligence mechanism for smart city security حسب S. Shitharth (12017480)

"…Moreover, the Reconciliate Multi-Agent Markov Learning (RMML) based classification algorithm is used to predict the intrusion with its appropriate classes. …"

Adaptive cooperative control of nonlinear multi-agent systems with uncertain time-varying control directions and dead-zone nonlinearity حسب Maryam Shahriari-kahkeshi (17269051)

Predicting Compression Modes and Split Decisions for HEVC Video Coding Using Machine Learning Techniques حسب Hassan, Mahitab Alaaeldin

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Bird’s Eye View feature selection for high-dimensional data حسب Samir Brahim Belhaouari (16855434)

"…BEV incorporates elements of Evolutionary Algorithms with a Genetic Algorithm to maintain a population of top-performing agents, Dynamic Markov Chain to steer the movement of agents in the search space, and Reinforcement Learning to reward and penalize agents based on their progress. …"

StackDPPred: Multiclass prediction of defensin peptides using stacked ensemble learning with optimized features حسب Muhammad Arif (769250)

"…Defensins are the type of AMPs that act as potential therapeutic drug agent and perform vital role in various biological process. …"

On the Optimization of Band Gaps in Periodic Waveguides حسب Jamil Renno (14070771)

"…<h3 dir="ltr">Purpose</h3><p dir="ltr">This work applies a computational framework for vibration attenuation in periodic structures by combining the established wave and finite element (WFE) method with nature-inspired optimization algorithms. …"

Resources Allocation for Drones Tracking Utilizing Agent-Based Proximity Policy Optimization حسب De Rochechouart, Maxence

"…This paper presents a reinforcement learning agent-based model that works by incorporating the MESA environment with the Stone Soup radar systems simulator. …"
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A Hybrid Deep Learning Model Using CNN and K-Mean Clustering for Energy Efficient Modelling in Mobile EdgeIoT حسب Dhananjay Bisen (19482454)

Large language models for code completion: A systematic literature review حسب Rasha Ahmad Husein (19744756)

"…Different techniques can achieve code completion, and recent research has focused on Deep Learning methods, particularly Large Language Models (LLMs) utilizing Transformer algorithms. …"

Synthesis of MVL Functions - Part I: The Genetic Algorithm Approach حسب Sarif, Bambang

"…Multiple-Valued Logic (MVL) has been used in the design of a number of logic systems, including memory, multi-level data communication coding, and a number of special purpose digital processors. …"
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The role of Reinforcement Learning in software testing حسب Amr Abo-eleneen (17032284)

"…</p><h3>Results</h3><p dir="ltr">This study highlights different software testing types to which RL has been applied, commonly used RL algorithms and architecture for learning, challenges faced, advantages and disadvantages of using RL, and the performance comparison of RL-based models against other techniques.…"

Optimized FPGA Implementation of PWAM-Based Control of Three—Phase Nine—Level Quasi Impedance Source Inverter حسب Syed Rahman (569240)

"…Since, PWAM control algorithm is more complex than PSCPWM, FPGA based implementation for PWAM control is discussed. …"

Deep Reinforcement Learning for Resource Constrained HLS Scheduling حسب Makhoul, Rim

"…In this work, we present a resource constrained scheduling approach that minimizes latency and subject to resource constraints using a deep Q learning algorithm. The actions and rewards for the proposed algorithm are selected carefully to guide the agent to its objective. …"
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