By Professor Hussein Abbass

Preprints

Hepworth A; Assaad Z; Wyatt A; Abbass H, 2026, Meaningful Human Command: Towards a New Model for Military Human-Robot Interaction, http://dx.doi.org/10.48550/arxiv.2604.06611

Wasswa H; Abbass H; Lynar T, 2026, How the Graph Construction Technique Shapes Performance in IoT Botnet Detection, http://dx.doi.org/10.48550/arxiv.2603.06654

Wasswa H; Abbass H; Lynar T, 2025, A Quantized VAE-MLP Botnet Detection Model: A Systematic Evaluation of Quantization-Aware Training and Post-Training Quantization Strategies, http://dx.doi.org/10.48550/arxiv.2511.03201

Eumi EM; Abbass H; Marcus N, 2025, SwarmChat: An LLM-Based, Context-Aware Multimodal Interaction System for Robotic Swarms, http://dx.doi.org/10.48550/arxiv.2509.16920

Akay T; Tolley H; Abbass H, 2025, Information-Theoretic Aggregation of Ethical Attributes in Simulated-Command, http://dx.doi.org/10.48550/arxiv.2507.12862

Wasswa H; Abbass H; Lynar T, 2025, Are GNNs Worth the Effort for IoT Botnet Detection? A Comparative Study of VAE-GNN vs. ViT-MLP and VAE-MLP Approaches, http://dx.doi.org/10.48550/arxiv.2505.17363

Wasswa H; Abbass H; Lynar T, 2025, Graph Attention Neural Network for Botnet Detection: Evaluating Autoencoder, VAE and PCA-Based Dimension Reduction, http://dx.doi.org/10.48550/arxiv.2505.17357

Wasswa H; Lynar T; Abbass H, 2025, Enhancing IoT-Botnet Detection using Variational Auto-encoder and Cost-Sensitive Learning: A Deep Learning Approach for Imbalanced Datasets, http://dx.doi.org/10.48550/arxiv.2505.01437

Wasswa H; Lynar T; Nanyonga A; Abbass H, 2025, IoT Botnet Detection: Application of Vision Transformer to Classification of Network Flow Traffic, http://dx.doi.org/10.48550/arxiv.2504.18781

Baxter DP; Hussein A; Abbass HA, 2024, Interpretability of Swarm State Tensors using Neural Machine Translation, http://dx.doi.org/10.36227/techrxiv.172297686.66710063/v1

Dam T; Anavatti SG; Abbass HA, 2023, Improving ClusterGAN Using Self-Augmented Information Maximization of Disentangling Latent Spaces, http://dx.doi.org/10.48550/arxiv.2107.12706

Dam T; Swami N; Anavatti SG; Abbass HA, 2023, Multi-Fake Evolutionary Generative Adversarial Networks for Imbalance Hyperspectral Image Classification, http://dx.doi.org/10.48550/arxiv.2111.04019

Liu J; Singh H; Elsayed S; Hunjet R; Abbass H, 2023, Planning-Assisted Context-Sensitive Autonomous Shepherding of Dispersed Robotic Swarms in Obstacle-Cluttered Environments, http://dx.doi.org/10.48550/arxiv.2301.10363

Hepworth A; Hussein A; Reid D; Abbass H, 2022, Contextually Aware Intelligent Control Agents for Heterogeneous Swarms, http://dx.doi.org/10.48550/arxiv.2211.12560

Hepworth A; Hussein A; Reid D; Abbass H, 2022, Swarm Analytics: Designing Information Markers to Characterise Swarm Systems in Shepherding Contexts, http://dx.doi.org/10.48550/arxiv.2208.12386

Dong X; Garratt MA; Anavatti SG; Abbass HA; Dong J, 2022, Lightweight Monocular Depth Estimation with an Edge Guided Network, http://dx.doi.org/10.48550/arxiv.2209.14829

Dam T; Ferdaus MM; Pratama M; Anavatti SG; Jayavelu S; Abbass HA, 2022, Latent Preserving Generative Adversarial Network for Imbalance classification, http://dx.doi.org/10.48550/arxiv.2209.01555

Nguyen DT; Kasmarik K; Abbass H, 2022, Fusing Interpretable Knowledge of Neural Network Learning Agents For Swarm-Guidance, http://dx.doi.org/10.48550/arxiv.2204.00272

Hepworth AJ; Baxter DP; Abbass HA, 2022, Onto4MAT: A Swarm Shepherding Ontology for Generalised Multi-Agent Teaming, http://dx.doi.org/10.48550/arxiv.2203.12955

Dong X; Garratt MA; Anavatti SG; Abbass HA, 2021, MobileXNet: An Efficient Convolutional Neural Network for Monocular Depth Estimation, http://dx.doi.org/10.48550/arxiv.2111.12334

Nguyen DT; Kasmarik KE; Abbass HA, 2021, Towards Interpretable ANNs: An Exact Transformation to Multi-Class Multivariate Decision Trees, http://dx.doi.org/10.48550/arxiv.2003.04675

Dong X; Garratt MA; Anavatti SG; Abbass HA, 2021, Towards Real-Time Monocular Depth Estimation for Robotics: A Survey, http://dx.doi.org/10.48550/arxiv.2111.08600

Simpson J; Oosthuizen R; Sawah SE; Abbass H, 2021, Agile, Antifragile, Artificial-Intelligence-Enabled, Command and Control, http://dx.doi.org/10.48550/arxiv.2109.06874

Dam T; Ferdaus MM; Anavatti SG; Jayavelu S; Abbass HA, 2021, Does Adversarial Oversampling Help us?, http://dx.doi.org/10.48550/arxiv.2108.10697

Hepworth A; yaxley K; Baxter D; Joiner K; Abbass H, 2020, Tracking Footprints in a Swarm: Information-Theoretic and Spatial Centre of Influence Measures, http://dx.doi.org/10.36227/techrxiv.12834002.v2

Nguyen HT; Garratt M; Bui LT; Abbass H, 2020, Disturbances in Influence of a Shepherding Agent is More Impactful than Sensorial Noise During Swarm Guidance, http://dx.doi.org/10.48550/arxiv.2008.12708

Dam T; Anavatti SG; Abbass HA, 2020, Mixture of Spectral Generative Adversarial Networks for Imbalanced Hyperspectral Image Classification, http://dx.doi.org/10.48550/arxiv.2009.13037

Elsayed S; Singh H; Debie E; Perry A; Campbell B; Hunjet R; Abbass H, 2020, Path Planning for Shepherding a Swarm in a Cluttered Environment using Differential Evolution, http://dx.doi.org/10.48550/arxiv.2008.12639

Nguyen HT; Nguyen TD; Tran VP; Garratt M; Kasmarik K; Anavatti S; Barlow M; Abbass HA, 2020, Continuous Deep Hierarchical Reinforcement Learning for Ground-Air Swarm Shepherding, http://dx.doi.org/10.48550/arxiv.2004.11543

Nguyen TD; Kasmarik KE; Abbass HA, 2020, Q-Learning with Differential Entropy of Q-Tables, http://dx.doi.org/10.48550/arxiv.2006.14795

Long NK; Sammut K; Sgarioto D; Garratt M; Abbass H, 2020, A Comprehensive Review of Shepherding as a Bio-inspired Swarm-Robotics Guidance Approach, http://dx.doi.org/10.48550/arxiv.1912.07796

Abbass HA; Elsawah S; Petraki E; Hunjet R, 2020, Machine Education: Designing semantically ordered and ontologically guided modular neural networks, http://dx.doi.org/10.48550/arxiv.2002.03841

Clayton NR; Abbass H, 2019, Machine Teaching in Hierarchical Genetic Reinforcement Learning: Curriculum Design of Reward Functions for Swarm Shepherding, https://arxiv.org/abs/1901.00949v1

Gee A; Abbass H, 2019, Transparent Machine Education of Neural Networks for Swarm Shepherding Using Curriculum Design, https://arxiv.org/abs/1903.09297v1

Abbass H; Harvey J; Yaxley K, 2018, Lifelong Testing of Smart Autonomous Systems by Shepherding a Swarm of Watchdog Artificial Intelligence Agents, http://dx.doi.org/10.48550/arxiv.1812.08960

Nguyen H; Tran V; Nguyen T; Garratt M; Kasmarik K; Barlow M; Anavatti S; Abbass H, 2018, Apprenticeship Bootstrapping Via Deep Learning with a Safety Net for UAV-UGV Interaction, http://dx.doi.org/10.48550/arxiv.1810.04344

Hussein A; Abbass H, 2018, Mixed Initiative Systems for Human-Swarm Interaction: Opportunities and Challenges, https://arxiv.org/abs/1808.06211v1

Hussein A; Ghignone L; Nguyen T; Salimi N; Nguyen H; Wang M; Abbass HA, 2018, Towards Bi-Directional Communication in Human-Swarm Teaming: A Survey, http://dx.doi.org/10.48550/arxiv.1803.03093

Abbass H; Greenwood G; Petraki E, 2018, The N-Player Trust Game and its Replicator Dynamics, http://dx.doi.org/10.48550/arxiv.1803.02443

Leu G; Abbass H, 2018, A Multi-Disciplinary Review of Knowledge Acquisition Methods: From Human to Autonomous Eliciting Agents, http://dx.doi.org/10.48550/arxiv.1802.09669

Tang J; Abbass HA, 2018, Behavioral Learning of Aircraft Landing Sequencing Using a Society of Probabilistic Finite State Machines, http://dx.doi.org/10.48550/arxiv.1802.10203

Leu G; Abbass H, 2018, Computational Red Teaming in a Sudoku Solving Context: Neural Network Based Skill Representation and Acquisition, http://dx.doi.org/10.48550/arxiv.1802.09660

Tang J; Leu G; Abbass H, 2018, Networking the Boids is More Robust Against Adversarial Learning, http://dx.doi.org/10.48550/arxiv.1802.10206

Leu G; Tang J; Abbass H, 2018, On the role of working memory in trading-off skills and situation awareness in Sudoku, http://dx.doi.org/10.48550/arxiv.1802.10079

Tang J; Petraki E; Abbass H, 2018, Shaping Influence and Influencing Shaping: A Computational Red Teaming Trust-based Swarm Intelligence Model, http://dx.doi.org/10.48550/arxiv.1802.09647

Chica M; Chiong R; Ramasco J; Abbass H, 2017, Effects of update rules on networked N-player trust game dynamics, http://dx.doi.org/10.48550/arxiv.1712.06875

Abbass HA; Leu G; Merrick K, 2016, A Review of Theoretical and Practical Challenges of Trusted Autonomy in Big Data, http://dx.doi.org/10.48550/arxiv.1604.00921

Iorio AW; Abbass HA; Gaidow S; Bender A, 2014, Visualizing Cognitive Moves for Assessing Information Perception Biases in Decision Making, http://dx.doi.org/10.48550/arxiv.1401.7193

Abbass H; Bender A; Dam H; Baker S; Whitacre JM; Sarker R, 2009, Computational Scenario-based Capability Planning, http://dx.doi.org/10.48550/arxiv.0907.0520

Whitacre JM; Bender A; Baker S; Fan Q; Sarker RA; Abbass H, 2009, Network Topology and Time Criticality Effects in the Modularised Fleet Mix Problem, http://dx.doi.org/10.48550/arxiv.0907.0597

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