Tipo di tesi
Tesi di laurea magistrale
Titolo
Q-learning-based distributed algorithm for hole recovery in Wireless Sensor Networks
Dipartimento
INGEGNERIA DELL'INFORMAZIONE
Corso di studi
ARTIFICIAL INTELLIGENCE AND DATA ENGINEERING
Parole chiave
- coverage
- coverage maximization
- hole recovery
- Q-learning
- reinforcement learning
- sensor node
- wireless sensor network
- WSN
Data inizio appello
28/04/2023
Riassunto (Inglese)
In this work, the implementation of a distributed algorithm based on Q-learning for hole recovery in Wireless Sensor Networks is described. Initially, a detailed analysis of the state-of-the-art for Hole Detection and Recovery has been carried out, focusing on Reinforcement Learning approaches. Then, a simulation environment for multi-agent reinforcement learning hole recovery algorithms has been implemented in Matlab. Subsequently, a state-of-the-art Q-learning based algorithm has been developed in the simulation environment, adding also a decaying rate for the exploration rate. Finally, Differential Evolution has been used for Hyperparameters Optimization.
