Design of a reinforcement learning-based lane keeping planning agent for automated vehicles B Kővári, F Hegedüs, T Bécsi Applied Sciences 10 (20), 7171, 2020 | 35 | 2020 |
Traffic signal control via reinforcement learning for reducing global vehicle emission B Kővári, L Szőke, T Bécsi, S Aradi, P Gáspár Sustainability 13 (20), 11254, 2021 | 14 | 2021 |
Deep reinforcement learning based approach for traffic signal control K Bálint, T Tamás, B Tamás Transportation Research Procedia 62, 278-285, 2022 | 13 | 2022 |
Reinforcement learning based control design for a floating piston pneumatic gearbox actuator T Bécsi, Á Szabó, B Kővári, S Aradi, P Gáspár IEEE Access 8, 147295-147312, 2020 | 12 | 2020 |
Multi-agent reinforcement learning for traffic signal control: A cooperative approach M Kolat, B Kővári, T Bécsi, S Aradi Sustainability 15 (4), 3479, 2023 | 11 | 2023 |
Reward design for intelligent intersection control to reduce emission B Kővári, B Pelenczei, S Aradi, T Bécsi IEEE Access 10, 39691-39699, 2022 | 10 | 2022 |
Mcts based approach for solving real-time railway rescheduling problem IF Lövétei, B Kővári, T Bécsi Periodica Polytechnica Transportation Engineering 49 (3), 283-291, 2021 | 7 | 2021 |
Policy gradient based control of a pneumatic actuator enhanced with monte carlo tree search B Kovari, T Becsi, A Szabo, S Aradi 2020 6th international conference on mechatronics and robotics engineering …, 2020 | 6 | 2020 |
Environment representations of railway infrastructure for reinforcement learning-based traffic control I Lövétei, B Kővári, T Bécsi, S Aradi Applied Sciences 12 (9), 4465, 2022 | 4 | 2022 |
Enhanced Experience Prioritization: A Novel Upper Confidence Bound Approach B Kővári, B Pelenczei, T Bécsi IEEE Access, 2023 | 1 | 2023 |
Multi-Agent Deep Reinforcement Learning (MADRL) for Solving Real-Time Railway Rescheduling Problem B Kővári, I Lövétei, S Aradi, T Bécsi | 1 | 2022 |
Strategic Data Navigation: Information Value-based Sample Selection CL Balogh, B Pelenczei, B Kővári, T Bécsi | | 2024 |
Deep Reinforcement Learning combined with RRT for trajectory tracking of autonomous vehicles. K Balint, AB Gergo, B Tamas Transportation Research Procedia 78, 246-253, 2024 | | 2024 |
Multi-Agent Reinforcement Learning for railway rescheduling B Kővári, CL Balogh, S Aradi 2023 IEEE 17th International Symposium on Applied Computational Intelligence …, 2023 | | 2023 |
Multi-Agent Reinforcement Learning for Traffic Signal Control: A Cooperative Approach. Sustainability 2023, 15, 3479 M Kolat, B Kovári, T Bécsi, S Aradi | | 2023 |
Designing Reward Functions in Multi-Agent Reinforcement Learning for Intelligent Intersection Control M Kolat, B Kővári, T Bécsi, S Aradi 2022 IEEE 20th Jubilee International Symposium on Intelligent Systems and …, 2022 | | 2022 |
Competitive Multi-Agent Reinforcement Learning for Traffic Signal Control B Kóvári, M Kolat, T Bécsi, S Aradi 2022 IEEE 20th Jubilee International Symposium on Intelligent Systems and …, 2022 | | 2022 |
Monte Carlo Tree Search to Compare Reward Functions for Reinforcement Learning B Kövári, B Pelenczei, T Bécsi 2022 IEEE 16th International Symposium on Applied Computational Intelligence …, 2022 | | 2022 |
Városi buszok útvonaltervezése Hangyakolónia módszer segítségével D Adonisz, H István, K Bálint | | 2021 |
Area Scanning with Reinforcement Learning and MCTS in Smart City Applications H Sándor, K Bálint, K Máté, G Tamás, V Dániel, R József, B György Repüléstudományi Közlemények 32 (2), 137–153-137–153, 2020 | | 2020 |