Learning automata with changing number of actions
IEEE Transactions on Systems, Man and Cybernetics
Learning automata: theory and applications
Learning automata: theory and applications
Priority-based target coverage in directional sensor networks using a genetic algorithm
Computers & Mathematics with Applications
Computer Networks: The International Journal of Computer and Telecommunications Networking
A memetic algorithm for extending wireless sensor network lifetime
Information Sciences: an International Journal
On coverage issues in directional sensor networks: A survey
Ad Hoc Networks
On coverage problems of directional sensor networks
MSN'05 Proceedings of the First international conference on Mobile Ad-hoc and Sensor Networks
Maximizing Lifetime of Target Coverage in Wireless Sensor Networks Using Learning Automata
Wireless Personal Communications: An International Journal
The Journal of Supercomputing
Learning automata-based algorithms for finding cover sets in wireless sensor networks
The Journal of Supercomputing
A learning automata-based solution to the target coverage problem in wireless sensor networks
Proceedings of International Conference on Advances in Mobile Computing & Multimedia
Wireless Personal Communications: An International Journal
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Recently, directional sensor networks have received a great deal of attention due to their wide range of applications in different fields. A unique characteristic of directional sensors is their limitation in both sensing angle and battery power, which highlights the significance of covering all the targets and, at the same time, extending the network lifetime. It is known as the target coverage problem that has been proved as an NP-complete problem. In this paper, we propose four learning automata-based algorithms to solve this problem. Additionally, several pruning rules are designed to improve the performance of these algorithms. To evaluate the performance of the proposed algorithms, several experiments were carried out. The theoretical maximum was used as a baseline to which the results of all the proposed algorithms are compared. The obtained results showed that the proposed algorithms could solve efficiently the target coverage problem.