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

Zenodo (CERN European Organization for Nuclear Research) 2026 Dataset Open access

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Authors: Martyniuk Maksym, Vakaliuk Tetiana
DOI: 10.5281/zenodo.18208952
Cited by: 0

Abstract

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.

Fields of Study & Subjects

Reinforcement Learning in Robotics Artificial Intelligence in Games Educational Games and Gamification

Publication details

Journal / source
Zenodo (CERN European Organization for Nuclear Research)
Publication date
10 January 2026
Language
EN
Document type
Dataset