Using IDS fitted Q to develop a real-time adaptive controller for dynamic resource provisioning in Cloud's virtualized environment. - Fouad Bahrpeyma; Ali Zakerolhosseini; Hassan Haghighi (Appl. Soft Comput., 2015)

An adaptive RL based approach for dynamic resource provisioning in Cloud virtualized data centers. - Fouad Bahrpeyma; Hassan Haghighi; Ali Zakerolhosseini (Computing, 2015)

A bipolar resource management framework for resource provisioning in Cloud's virtualized environment. - Fouad Bahrpeyma; Hassan Haghighi; Ali Zakerolhosseini (Appl. Soft Comput., 2016)

Active fuzzy modeling for estimating problems in hydrocarbon reservoirs. - Mehdi Fasanghari; Fouad Bahrpeyma; Fariborz Jolai (Neural Comput. Appl., 2016)

Multi-Resolution Forecast Aggregation for Time Series in Agri Datasets. - Fouad Bahrpeyma; Mark Roantree; Andrew McCarren (AICS, 2017)

Multistep-ahead Prediction: A Comparison of Analytical and Algorithmic Approaches. - Fouad Bahrpeyma; Mark Roantree; Andrew McCarren (DaWaK, 2018)

An Application of Reinforcement Learning in Industrial Cyber-Physical Systems. - David Heik; Fouad Bahrpeyma; Dirk Reichelt (OVERLAY@AI*IA, 2022)

A Concept for QoS Management in SOA-Based SoS Architectures. - Ingolf Gehrhardt; Fouad Bahrpeyma; Dirk Reichelt (ISDA (1), 2022)

Dynamic Job Shop Scheduling in an Industrial Assembly Environment Using Various Reinforcement Learning Techniques. - David Heik; Fouad Bahrpeyma; Dirk Reichelt (ISDA (3), 2022)

A review of the applications of multi-agent reinforcement learning in smart factories. - Fouad Bahrpeyma; Dirk Reichelt (Frontiers Robotics AI, 2022)

An end to end workflow for synthetic data generation for robust object detection*. - Johannes Metzler; Fouad Bahrpeyma; Dirk Reichelt (INDIN, 2023)

Solving a Dynamic Scheduling Problem for a Manufacturing System with Reinforcement Learning. - David Heik; Fouad Bahrpeyma; Dirk Reichelt (IntelliSys (2), 2023)

Application of Multi-agent Reinforcement Learning to the Dynamic Scheduling Problem in Manufacturing Systems. - David Heik; Fouad Bahrpeyma; Dirk Reichelt (LOD (2), 2023)

Application of Inhomogeneous QMIX in Various Architectures to Solve Dynamic Scheduling in Manufacturing Environments. - David Heik; Alexander Böhm 006; Fouad Bahrpeyma; Dirk Reichelt (INDIN, 2024)

Positioning Stabilization With Reinforcement Learning for Multi-Step Robot Positioning Tasks in Nvidia Omniverse. - Abishek Sunilkumar; Fouad Bahrpeyma; Dirk Reichelt (INDIN, 2024)

A Meta-learner approach to multistep-ahead time series prediction. - Fouad Bahrpeyma; Vuong M. Ngo; Mark Roantree; Andrew McCarren (Int. J. Data Sci. Anal., 2025)