Category Archives: News

Paper accepted for presentation at the 5th International Conference on Communication and Computational Technologies (ICCCT 2023)

Paper “Modified Artificial Bee Colony Algorithm for Tuning Simple LSTM for Multivariate Time-Series Forecasting,” by J. Krstovic, N. Bacanin, M. Zivkovic, A. Bozovic, M.S. Stankovic, M. Antonijevic, and T. Bezdan, has been accepted for presentation at the 5th International Conference on Communication and Computational Technologies (ICCCT 2023) to be held in January 2023.

Paper accepted in journal Automatica!

Paper “Distributed Consensus-Based Multi-Agent Temporal-Difference Learning“, by M.S. Stanković, M. Beko and S.S. Stanković, has been published in Automatica!

The paper proposes two new distributed consensus-based algorithms for temporal-difference learning in multi-agent Markov decision processes. The algorithms are of off-policy type and are aimed at linear approximation of the value function. Restricting agents’ observations to local data and communications to their small neighborhoods, the algorithms consist of: a) local updates of the parameter estimates based on either the standard TD(λ) or the emphatic ETD(λ) algorithm, and b) dynamic consensus scheme implemented over a time-varying lossy communication network. The algorithms are completely decentralized, allowing efficient parallelization and applications where the agents may have different behavior policies and different initial state distributions while evaluating a common target policy. It was proved under nonrestrictive assumptions that the proposed algorithms weakly converge to the solutions of the mean ordinary differential equation (ODE) common for all the agents. It was also proved that the whole system may be stabilized by a proper choice of the network and that the parameter estimates weakly converge to consensus. Simulation results were also presented, illustrating the main properties of the algorithms and providing comparisons with similar existing schemes.

Paper presented at the 4th International Conference on Innovative Data Communication Technology and Application (ICIDCA 2022)

Paper “Tuning Multi-Layer Perceptron by Hybridized Arithmetic Optimization Algorithm for Healthcare 4.0”, by Marko Stankovic, J. Gavrilovic, D. Jovanovic, M. Zivkovic, M. Antonijevic, N. Bacanin, and M.S. Stankovic, has been presented at the 4th International Conference on Innovative Data Communication Technology and Application (ICIDCA), 2022.

Published paper in journal Mathematics!

Paper “Tuning Machine Learning Models Using a Group Search Firefly Algorithm for Credit Card Fraud Detection“, by D. Jovanovic, M. Antonijevic, M.S. Stankovic, M. Zivkovic, M. Tanaskovic and N. Bacanin, has been published in Mathematics!

The research published in the paper proposes a hybrid machine learning and swarm metaheuristic approach to address the challenge of credit card fraud detection. The novel, enhanced firefly algorithm, named group search firefly algorithm, was devised and then used to a tune support vector machine, an extreme learning machine, and extreme gradient-boosting machine learning models. Boosted models were tested on the real-world credit card fraud detection dataset. The performance of the proposed group search firefly metaheuristic was compared with other recent state-of-the-art approaches. The experimental findings clearly demonstrate that the models tuned by the proposed algorithm obtained superior results in comparison to other models hybridized with competitor metaheuristics.