بدائل البحث:
agent learning » student learning (توسيع البحث)
te algorithm » rd algorithm (توسيع البحث), deer algorithm (توسيع البحث), _ algorithms (توسيع البحث)
element te » elementi per (توسيع البحث)
agent learning » student learning (توسيع البحث)
te algorithm » rd algorithm (توسيع البحث), deer algorithm (توسيع البحث), _ algorithms (توسيع البحث)
element te » elementi per (توسيع البحث)
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Multi-Agent Learning of Strategies in Abstract Argumentation Mechanisms
منشور في 2009"…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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3
Deep Reinforcement Learning for Resource Constrained HLS Scheduling
منشور في 2022"…We used a deep neural network to train the agent and in order to learn the the Q-values. …"
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masterThesis -
4
Single channel speech denoising by DDPG reinforcement learning agent
منشور في 2025"…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. …"
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Multi Agent Reinforcement Learning Approach for Autonomous Fleet Management
منشور في 2019احصل على النص الكامل
doctoralThesis -
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A Parallel Neural Networks Algorithm for the Clique Partitioning Problem
منشور في 2002"…The clique partitioning problem has important applications in many areas including VLSI design automation, scheduling, and resources allocation. In this paper we present a parallel algorithm to solve the above problem for arbitrary graphs using a Hopfield Neural Network model of computation. …"
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A Neural Networks Algorithm for the Minimum Colouring Problem Using FPGAs†
منشور في 2010"…The proposed algorithm has a time complexity of O(1) for a neural network with n vertices and k colours. …"
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Experimental evaluation of multi-agent reinforcement learning in real-world scale-free networks
منشور في 2010"…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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9
Multi-Agent Meta Reinforcement Learning for Reliable and Low-Latency Distributed Inference in Resource-Constrained UAV Swarms
منشور في 2025"…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. …"
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10
A conjugate self-organizing migration (CSOM) and reconciliate multi-agent Markov learning (RMML) based cyborg intelligence mechanism for smart city security
منشور في 2023"…Moreover, the Reconciliate Multi-Agent Markov Learning (RMML) based classification algorithm is used to predict the intrusion with its appropriate classes. …"
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Bird’s Eye View feature selection for high-dimensional data
منشور في 2023"…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. …"
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StackDPPred: Multiclass prediction of defensin peptides using stacked ensemble learning with optimized features
منشور في 2024"…Defensins are the type of AMPs that act as potential therapeutic drug agent and perform vital role in various biological process. …"
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Resources Allocation for Drones Tracking Utilizing Agent-Based Proximity Policy Optimization
منشور في 2023"…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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The role of Reinforcement Learning in software testing
منشور في 2023"…</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.…"
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Prediction of EV Charging Behavior Using Machine Learning
منشور في 2021"…Using data-driven tools and machine learning algorithms to learn the EV charging behavior can improve scheduling algorithms. …"
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Reinforcement Learning-Based School Energy Management System
منشور في 2020"…After cloning the baseline strategy, the agent learns with proximal policy optimization in an actor-critic framework. …"
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Recent advances on artificial intelligence and learning techniques in cognitive radio networks
منشور في 2015"…The literature survey is organized based on different artificial intelligence techniques such as fuzzy logic, genetic algorithms, neural networks, game theory, reinforcement learning, support vector machine, case-based reasoning, entropy, Bayesian, Markov model, multi-agent systems, and artificial bee colony algorithm. …"
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Drones Tracking Adaptation Using Reinforcement Learning: Proximal Policy optimization
منشور في 2023"…Our results demonstrate the successful learning capability of the PPO agent over time, enabling it to suggest the optimal Q value by effectively capturing the policy of appropriate rewards under varying environmental conditions. …"
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