Summary of Multi-agent Reinforcement Learning Strategy to Maximize the Lifetime Of Wireless Rechargeable, by Bao Nguyen
Multi-agent reinforcement learning strategy to maximize the lifetime of Wireless Rechargeable
by Bao Nguyen
First submitted to arxiv on: 21 Nov 2024
Categories
- Main: Machine Learning (cs.LG)
- Secondary: Computer Vision and Pattern Recognition (cs.CV); Computer Science and Game Theory (cs.GT); Multiagent Systems (cs.MA)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The proposed generalized charging framework for multiple mobile chargers aims to maximize network lifetime and ensure target coverage and connectivity in large-scale Wireless Rechargeable Sensor Networks (WRSNs). The framework leverages a multi-point charging model, enabling MCs to charge multiple sensors simultaneously at each location. To achieve this, the thesis proposes a Decentralized Partially Observable Semi-Markov Decision Process (Dec POSMDP) model that promotes cooperation among MCs and detects optimal charging locations based on real-time network information. Additionally, the proposal allows for the application of reinforcement algorithms to different networks without requiring extensive retraining. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary Imagine a world where sensors can be charged wirelessly, without needing to be plugged in. This paper proposes a way to make that happen. It’s all about creating a system where multiple chargers can work together to keep sensors powered up and connected. The idea is to have these chargers find the best spots to recharge the sensors, while also making sure they’re all working together seamlessly. The scientists used special algorithms to figure out how to get this done efficiently. Now, people can start building bigger networks with many more sensors, without worrying about running out of power. |
