- M.S. Stanković, M. Beko and S.S. Stanković, “Distributed Value Function Approximation for Collaborative Multi-Agent Reinforcement Learning”, IEEE Transactions on Control of Network Systems, 8(3), pp. 1270 – 1280, 2021.
- D. Dašić, N. Ilić, M. Vučetić, M. Perić, M. Beko and M.S. Stanković, “Distributed Spectrum Management in Cognitive Radio Networks by Consensus-Based Reinforcement Learning,” Sensors, 21(9), 2970. 2021.
- M.S. Stanković, N. Ilić and S.S. Stanković, “Decentralized Consensus-Based Estimation and Target Tracking“, Academic Mind, Belgrade, 2021, ISBN 978-86-7466-859-7.
- A. Ćuk, T. Bezdan, N. Bačanin, M. Živković, K. Venkatachalam, T. A. Rashid, and V. K. Devi, “Feedforward Multi-Layer Perceptron Training by Hybridized Method between Genetic Algorithm and Artificial Bee Colony“, in “Data Science and Data Analytics – Opportunities and Challenges“ edited by Amit Kumar Tyagi, Chapman and Hall/CRC, 2021.
- R. Boffadossi, L. Fagiano, A. Cataldo, M. Tanaskovic, and M. Lauricella, “Advanced Hierarchical Predictive Routing Control of a Smart De-Manufacturing Plant,” European Control Conference (ECC), July 2021.
- A. Ćuk, U. Dragović, M. Tanasković, N. Bačanin and M.S. Stanković, “Obuka perceptrona hibridizovanom metodom između genetskog algoritma i Firefly algoritma”, YUINFO 2021 Conference, 2021.
- L. Fagiano, M. Tanaskovic, L. C. Mallitasig, A. Cataldo and R. Scattolini, “Hierarchical routing control in discrete manufacturing plants via model predictive path allocation and greedy path following,” 2020 59th IEEE Conference on Decision and Control (CDC), Jeju Island, Korea (South), 2020, pp. 5546-5551, doi: 10.1109/CDC42340.2020.9303933.
- M. S. Stanković, M. Beko, N. Ilić and S. S. Stanković, “Distributed Multi-Agent Reinforcement Learning Algorithm based on Gradient Correction“, Proc. of 7th IcETRAN, Belgrade, 2020.