Dataset: Q-learning Q-tables for 'A drone simulator with smart objectives, developed using artificial intelligence technologies to implement user stories'

This dataset contains tabular Q-learning Q-tables produced in an Unreal Engine 5 drone simulator with intelligent adaptive targets. The data represent state-action values (Q-values) for three high-level actions (TowardGoal, TowardCover, RandomMove) across discretised environment sections (sectionKey). Files included: RLData.json, initial (pre-training) Q-table used to initialise the agent policy. RLDataTrained.json, Q-table after 20 training episodes, reflecting learned behaviour.