Measuring Neuronal Branching Patterns Using Model-Based Approach. - Artur Luczak (Frontiers Comput. Neurosci., 2010)

Context-switching and adaptation: Brain-inspired mechanisms for handling environmental changes. - Eric Chalmers; Edgar Bermudez Contreras; Brandon Robertson; Artur Luczak; Aaron J. Gruber (IJCNN, 2016)

Computational Properties of the Hippocampus Increase the Efficiency of Goal-Directed Foraging through Hierarchical Reinforcement Learning. - Eric Chalmers; Artur Luczak; Aaron J. Gruber (Frontiers Comput. Neurosci., 2016)

Creation of a deep convolutional auto-encoder in Caffe. - Volodymyr Turchenko; Artur Luczak (IDAACS, 2017)

Learning to Predict Consequences as a Method of Knowledge Transfer in Reinforcement Learning. - Eric Chalmers; Edgar Bermudez Contreras; Brandon Robertson; Artur Luczak; Aaron J. Gruber (IEEE Trans. Neural Networks Learn. Syst., 2018)

A Deep Convolutional Auto-encoder with Pooling - Unpooling Layers in Caffe. - Volodymyr Turchenko; Eric Chalmers; Artur Luczak (Int. J. Comput., 2019)

Biologically-inspired neuronal adaptation improves learning in neural networks. - Yoshimasa Kubo; Eric Chalmers; Artur Luczak (CoRR, 2022)

Reinforcement Learning with Brain-Inspired Modulation can Improve Adaptation to Environmental Changes. - Eric Chalmers; Artur Luczak (CoRR, 2022)

Hippocluster: an efficient, hippocampus-inspired algorithm for graph clustering. - Eric Chalmers; Artur Luczak (CoRR, 2022)

Combining backpropagation with Equilibrium Propagation to improve an Actor-Critic reinforcement learning framework. - Yoshimasa Kubo; Eric Chalmers; Artur Luczak (Frontiers Comput. Neurosci., 2022)

Neurons learn by predicting future activity. - Artur Luczak; Bruce L. McNaughton; Yoshimasa Kubo (Nat. Mach. Intell., 2022)

Reinforcement Learning with Brain-Inspired Modulation Improves Adaptation to Environmental Changes. - Eric Chalmers; Artur Luczak (ICAISC (1), 2023)

Hippocluster: An efficient, hippocampus-inspired algorithm for graph clustering. - Eric Chalmers; Aaron J. Gruber; Artur Luczak (Inf. Sci., 2023)

Memory Augmented Multi-agent Reinforcement Learning for Cooperative Environment. - Maryam Kia; Jordan Cramer; Artur Luczak (ICAISC (3), 2024)

Neurons as autonomous agents: A biologically inspired framework for cognitive architectures in artificial intelligence. - Artur Luczak (Cogn. Syst. Res., 2025)