Automated healthcare IoT systems demand secure, low-latency, and energy-efficient computation—capabilities well-supported by fog computing. Effective selection of fog nodes is critical for maximizing ...
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Motivated by "A Deep Reinforcement Learning Framework for the Financial Portfolio Management Problem" by Jiang et. al. 2017 [1]. In this project: Implement three state-of-art continous deep ...
Greenhouse vegetable production was a complex agricultural system influenced by multiple interrelated environmental and management factors. Its irrigation control was a critical but not singularly ...
Want your business to show up in Google’s AI-driven results? The same principles that help you rank in Google Search still matter – but AI introduces new dimensions of context, reputation, and ...
How do you convert real agent traces into reinforcement learning RL transitions to improve policy LLMs without changing your existing agent stack? Microsoft AI team releases Agent Lightning to help ...
Abstract: Large-scale overlapping problems (LSOPs) pose significant challenges in optimization due to the intricate interactions among the subcomponents. Traditional decomposition-based cooperative co ...
Abstract: This paper presents a simulation-based benchmarking analysis of three reinforcement learning (RL) algorithms—Soft Actor-Critic (SAC), Deep Q-Network (DQN), and Proximal Policy Optimization ...
This project uses reinforcement learning techniques to optimize home energy management systems, enabling intelligent energy scheduling and cost optimization. It supports multiple advanced RL ...
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