This work analyses the performance of Reinforcement Learning (RL) versus Swarm Intelligence (SI) for coordinating multiple unmanned High Altitude Platform Stations (HAPS) for communications area coverage. It builds upon previous work which looked at various elements of both algorithms. The main aim of this paper is to address the continuous state-space challenge within this work by using partitioning to manage the high dimensionality problem.

Anicho, O., Charlesworth, P.B., Baicher, G.S. et al. Reinforcement learning versus swarm intelligence for autonomous multi-HAPS coordination. SN Appl. Sci. 3, 663 (2021).

This paper examines the implementation of solar-powered High Altitude Platform Stations (HAPS) for rural broadband connectivity. It outlines some technical considerations and concepts associated with implementing HAPS as a communications infrastructure. To realise the potentials of solar HAPS for rural broadband connectivity, some key technology, business and policy questions must be addressed.

O. Anicho, P. B. Charlesworth, G. S. Baicher and A. Nagar, "Implementing Solar-Powered HAPS for Rural broadband Connectivity: Concepts, Challenges & Mitigation," 2020 IEEE Global Humanitarian Technology Conference (GHTC), 2020, pp. 1-8, doi: 10.1109/GHTC46280.2020.9342894.

This paper examines Situation Awareness (SA) as a factor in addressing routing challenges in HAPS/UAV based networks especially in multi-HAPS/UAV implementations.

O. Anicho, P. B. Charlesworth, G. S. Baicher and A. Nagar, "Situation Awareness and Routing Challenges in Unmanned HAPS/UAV based Communications Networks," 2020 International Conference on Unmanned Aircraft Systems (ICUAS), 2020, pp. 1175-1182, doi: 10.1109/ICUAS48674.2020.9214015.

This paper examines the impact of exploration–exploitation dilemma on the application of RL for coordinating multiple UAVs/HAPS.

Anicho O., Charlesworth P.B., Baicher G.S., Nagar A.K. (2020) Reinforcement Learning for Multiple HAPS/UAV Coordination: Impact of Exploration–Exploitation Dilemma on Convergence. In: Nagar A., Deep K., Bansal J., Das K. (eds) Soft Computing for Problem Solving 2019. Advances in Intelligent Systems and Computing, vol 1138. Springer, Singapore. https://doi.org/10.1007/978-981-15-3290-0_12