With the advent of Reinforcement Learning(RL)and its continuous progress,state-of-the-art RL systems have come up for many challenging and real-world *** the scope of this area,various techniques are found in the *** ...
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With the advent of Reinforcement Learning(RL)and its continuous progress,state-of-the-art RL systems have come up for many challenging and real-world *** the scope of this area,various techniques are found in the *** such notable technique,Multiple Deep Q-Network(DQN)based RL systems use multiple DQN-based-entities,which learn together and communicate with each *** learning has to be distributed wisely among all entities in such a scheme and the inter-entity communication protocol has to be carefully *** more complex DQNs come to the fore,the overall complexity of these multi-entity systems has increased many folds leading to issues like difficulty in training,need for high resources,more training time,and difficulty in fine-tuning leading to performance *** a cue from the parallel processing found in the nature and its efficacy,we propose a lightweight ensemble based approach for solving the core RL *** uses multiple binary action DQNs having shared state and *** benefits of the proposed approach are overall simplicity,faster convergence and better performance compared to conventional DQN based *** approach can potentially be extended to any type of DQN by forming its *** extensive experimentation,promising results are obtained using the proposed ensemble approach on OpenAI Gym tasks,and Atari 2600 games as compared to recent *** proposed approach gives a stateof-the-art score of 500 on the Cartpole-v1 task,259.2 on the LunarLander-v2 task,and state-of-the-art results on four out of five Atari 2600 games.
Skin cancer presents a significant public health concern, necessitating early detection and intervention to mitigate life-threatening consequences. Despite its prevalence, skin cancer is not always given the attention...
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The aim of the article is to present the adopted concept for the construction of an unmanned aircraft delivering a defibrillator to save people with sudden cardiac arrest. The concept is based on an unmanned aircraft ...
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Given the global rise in antibiotic resistance, antimicrobial peptides (AMPs) provide a viable substitute for traditional antibiotics. Through a comparison of transformer-based, deep learning (DL), and machine learnin...
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In modern cloud environments, Docker containers have become a cornerstone for efficient application deployment, enabling microservices architectures and seamless scalability. However, large-scale Docker environments p...
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Next-Generation Crowdsensing Networks (NGCNs) have become increasingly critical for smart cities, where data privacy and quality are pivotal concerns. Traditional trust mechanisms in crowdsensing mainly rely on static...
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In the Polish railway sector is a visible increasing dynamics of employee turnover. It is a challenge in the current management of railroad personnel. Due to that, new tools are introduced in the teaching process of t...
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This research introduces a sophisticated framework for real-time video captioning that seamlessly integrates a cohesive ensemble of machine learning *** development of open-domain video descriptions that can manage va...
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Plastic is the second largest amount of waste in Indonesia, reaching 17.3% of the total waste of 28.6 million tons for 2021. The type of plastic that is most often recycled is plastic bottle packaging. Plastic waste t...
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There has been a growing interest in using natural alternatives to synthetic additives in animal feed. This study aimed to examine the physicochemical properties of signal grass (Brachiaria decumbens) and its cost-ben...
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