The latest amendment 802.11ax to the IEEE 802.11 standard, better known by its commercial name Wi-Fi 6, includes a feature that aims at improving the spatial reuse of a channel: each device can adapt its Clear Channel Assessment sensitivity threshold and its transmission power. In this paper, we use the Multi-Armed Bandit (MAB) framework to propose a centralized solution to dynamically adapt these parameters. We propose a new approach based on a Gaussian mixture to sample new network configurations, a specific reward function that prevents starvations when maximized, as well as a method based on Thompson Sampling to select the best network configuration. We evaluate our solution using the network simulator ns-3 and different topologies. Simulation results confirm the large benefits that 802.11ax may bring to spatial reuse. They also demonstrate the efficiency of our solution in finding appropriate parameter configurations that significantly improve the quality of service of the networks. CCS CONCEPTS • General and reference → Performance; • Networks → Network control algorithms; Network simulations; Wireless local area networks; • Theory of computation → Bayesian analysis; Reinforcement learning.