Worldwide Publications on Shepherding

Books, Journal and Conference Manuscripts

Shepherding: Survey Papers and Books

Shepherding: Live Experimental Data

Shepherding: Modelling and Simulation

  • Himo, R., Ogura, M., & Wakamiya, N. (2022). Iterative algorithm for shepherding unresponsive sheep. Mathematical Biosciences and Engineering, 19(4), 3509–3525. DOI:doi.org/10.3934/mbe.2022162 [Open Access Version]
  • Campbell, B., El-Fiqi, H., Hunjet, R., & Abbass, H. A. (2021, July). Distributed Multi-agent Shepherding with Consensus. In International Conference on Swarm Intelligence (pp. 168-181). Springer, Cham. [Restricted Access]
  • El-Fiqi, H., Campbell, B., Elsayed, S., Perry, A., Singh, H. K., Hunjet, R., & Abbass, H. A. (2020). The Limits of Reactive Shepherding Approaches for Swarm Guidance. IEEE Access, 8, 214658-214671. .DOI:doi.org/10.1109/ACCESS.2020.3037325 [Open Access Version]
  • El-Fiqi, H., Campbell, B., Elsayed, S., Perry, A., Singh, H. K., Hunjet, R., & Abbass, H. (2020, July). A preliminary study towards an improved shepherding model. In Proceedings of the 2020 Genetic and Evolutionary Computation Conference Companion (pp. 75-76). DOI:doi.org/10.1145/3377929.3390067 [Open Access Version]
  • Nguyen, H. T., Garratt, M., Bui, L. T., & Abbass, H. (2020). Disturbances in influence of a shepherding agent is more impactful than sensorial noise during swarm guidance. IEEE Symposium Series on Computational Intelligence, Canberra, Australia. DOI:doi.org/10.1109/SSCI47803.2020.9308448 [Open Access arXiv Version]
  • Tsunoda, Y., Ishitani, M., Sueoka, Y., Osuka, K. (2019). Analysis of sheepdog-type navigation for a sheep model with dynamics. The Twenty-Fourth International Symposium on Artificial Life and Robotics (AROB 24th 2019), 499-503.  [Open Access Version]
  • Tsunoda, Y., Ishitani, M., Sueoka, Y., Osuka, K. (2019). Analysis of sheepdog-type navigation for minimal sheep model. Swarm 2019, 197-200.  [Open Access Version]

Shepherding: Navigation and Control

  • 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. IEEE Symposium Series on Computational Intelligence, Canberra, Australia. DOI:doi.org/10.1109/SSCI47803.2020.9308572 [Open Access arXiv Version]
  • Singh H., Campbell B., Elsayed S., Perry A., Huntjet R. & Abbass H.A. (2019). Modulation of Force Vectors for Effective Shepherding of a Swarm: A Bi-Objective Approach. IEEE Congress on Evolutionary Computation, Wellington, New Zealand. DOI:doi.org/10.1109/CEC.2019.8790228 [Author Version]

Shepherding: Robotics

  • Auletta, F., Fiore, D., Richardson, M. J., & di Bernardo, M. (in-press). Herding stochastic autonomous agents via local control rules and online global target selection strategies. Autonomous Robots, 2021. DOI:doi.org/ [Open Access arXiv Version]
  • Tsunoda, Y., Sueoka, Y., Wada, T., & Osuka, K. (2020, January). Sheepdog-type robot navigation: Experimental verification based on a linear model. In 2020 IEEE/SICE International Symposium on System Integration (SII) (pp. 1144-1149). IEEE. DOI:doi.org/10.1109/SII46433.2020.9026218 [Open Access]
  • Tsunoda, Y., Sueoka, Y., & Osuka, K. (2019). Exploration of sheepdog controller for sheep flock navigation based on the model derived from a real shepherding. In 9th International Symposium on Adaptive Motion of Animals and Machines (AMAM 2019) (No. CONF). DOI:doi.org/10.5075/epfl-BIOROB-AMAM2019-56 [Open Access]
  • Tsunoda, Y., Sueoka, Y., Sato, Y., & Osuka, K. (2018). Analysis of local-camera-based shepherding navigation. Advanced Robotics, 32(23), 1217-1228. DOI:doi.org/10.1080/01691864.2018.1539410 [Open Access [Author Copy]
  • Tsunoda, Y., Sueoka, Y., & Osuka, K. (2017, December). On statistical analysis for shepherd guidance system. In 2017 IEEE International Conference on Robotics and Biomimetics (ROBIO) (pp. 1246-1251). DOI:doi.org/10.1109/ROBIO.2017.8324588 [Restricted Access]

Shepherding: Indicators and Markers

Shepherding: Communication

  • Mohamed, R. E., Elsayed, S., Hunjet, R., & Abbass, H. (2021, November). Deep Learning For Noisy Communication System. In 2021 31st International Telecommunication Networks and Applications Conference (ITNAC) (pp. 40-47). IEEE. DOI:doi.org/10.1109/ITNAC53136.2021.9652171 [Author Copy]
  • Mohamed, R. E., Elsayed, S., Hunjet, R., & Abbass, H. (2021, June). A Graph-based Approach for Shepherding Swarms with Limited Sensing Range. In 2021 IEEE Congress on Evolutionary Computation (CEC) (pp. 2315-2322). IEEE. DOI:doi.org/10.1109/CEC45853.2021.9504706 [Author Copy]

Shepherding: Machine Learning

  • Hussein A., Petraki E., El-Sawah S., & Abbass, H.A. (2022). Autonomous Swarm Shepherding Using Curriculum-Based Reinforcement Learning. AAMAS 2022, Auckland, NZ. DOI:doi.org/ [Author Version]
  • Zhi, J., & Lien, J. M. (2021). Learning to herd agents amongst obstacles: Training robust shepherding behaviors using deep reinforcement learning . IEEE Robotics and Automation Letters, 6(2), 4163-4168. DOI:doi.org/10.1109/LRA.2021.3068955  [Open Access arXiv Version]
  • Debie, E., Singh, H., Elsayed, S., Perry, A., Hunjet, R., & Abbass, H.A. (2020). A Neuro-Evolution Approach to Shepherding Swarm Guidance in the Face of Uncertainty. In 2021 IEEE International Conference on Systems, Man, and Cybernetics (SMC) (pp. 2634-2641). IEEE. DOI:doi.org/10.1109/SMC52423.2021.9659082 [Author Version]
  • Nguyen T., Liu J., Nguyen H., Kasmarik K., Anavatti S., Garratt M., & Abbass, H.A. (2020). Perceptron-Learning for Scalable and Transparent Dynamic Formation in Swarm-on-Swarm Shepherding. Joint International Conference on Neural Networks (IJCNN 2020), Glasgow, UK. DOI:doi.org/10.1109/IJCNN48605.2020.9207539 [Author Version]
  • Nguyen T., Nguyen H., Tan V., Garratt M., Kasmarik K., Anavatti S., Barlow M., & Abbass, H.A. (2020). Continuous Deep Hierarchical Reinforcement Learning for Ground-Air Swarm Shepherding. arXiv.[Open Access arXiv Version]
  • Nguyen H., Garratt M., Bui L., & Abbass, H.A. (2019). Apprenticeship Learning for Continuous State Spaces and Actions in a Swarm-Guidance Shepherding Task. IEEE Symposium Series on Computational Intelligence, (IEEE SSCI19), Xiamen, China. DOI:doi.org/10.1109/SSCI44817.2019.9002756 [Author Version]
  • Gee A. and Abbass H.A. (2019).Transparent Machine Education of Neural Networks for Swarm Shepherding Using Curriculum Design. International Joint Conference on Neural Networks (IJCNN), Budapest, Hungary. DOI:doi.org/ [Open Access arXiv Version]
  • Clayton N. and Abbass H.A. (2019).Machine Teaching in Hierarchical Genetic Reinforcement Learning: Curriculum Design of Reward Functions for Swarm Shepherding. IEEE Congress on Evolutionary Computation, Wellington, New Zealand. DOI:doi.org/10.1109/CEC.2019.8790157 [Open Access arXiv Version]

Shepherding: Human-Machine Teaming

  • Abbass, H., Petraki, E., and Hunjet, R. (2022). JSwarm: A Jingulu-Inspired Human-AI-Teaming Language for Context-Aware Swarm Guidance, Frontiers Physics. https://www.frontiersin.org/articles/10.3389/fphy.2022.944064/full [Open Access Version]
  • A. J. Hepworth, D. P. Baxter and H. A. Abbass, Onto4MAT: A Swarm Shepherding Ontology for Generalized Multiagent Teaming. IEEE Access, vol. 10, pp. 59843-59861, 2022, doi:10.1109/ACCESS.2022.3180032. [Open Access Version]
  • Baxter, D. P., Hepworth, A. J., Joiner, K. F., and H. A. Abbass, On the premise of a swarm guidance ontology for human-swarm teaming. Proceedings of the Human Factors and Ergonomics Society Annual Meeting (Vol. 66, No. 1, pp. 2249-2253). Sage CA: Los Angeles, CA: SAGE Publications. doi:10.1177/1071181322661541. [Open Access Version]
  • Hepworth, A. J., Baxter, D. P., Hussein, A., Yaxley, K. J., Debie, E., & Abbass, H. A. (2021). Human-swarm-teaming transparency and trust architecture. IEEE/CAA Journal of Automatica Sinica, 8(7), 1281-12950. DOI:doi.org/10.1109/JAS.2020.1003545 [Author Copy]
  • Auletta, F., di Bernardo, M., & Richardson, M. J. (2021). Human-inspired strategies to solve complex joint tasks in multi agent systems. IFAC-PapersOnLine, 54(17), 105-110. DOI:doi.org/10.1016/j.ifacol.2021.11.033 [Open Access Version]
  • Nalepka, P., Silva, P. L., Kallen, R. W., Shockley, K., Chemero, A., Saltzman, E., & Richardson, M. J. (2021). Task dynamics define the contextual emergence of human corralling behaviors. PloS one, 16(11), e0260046. DOI:doi.org/10.1371/journal.pone.0260046 [Open Access Version]
  • Debie, E., El-fiqi H., Fidock, J., Barlow, M., Merrick, K., Anavatti, S., Garratt, M., & Abbass H.A. (2021). A Trust-Based, Adjustable, Autonomous Recommender System for Reconnaissance Tasks using a Swarm of UAVs and Asynchronous Shepherding. Human-Intelligent Systems Integration, 3(2), 175-186. DOI:doi.org/10.1007/s42454-020-00024-w [Author Version]
  • Rigoli, L. M., Nalepka, P., Douglas, H., Kallen, R. W., Hosking, S., Best, C., Saltzman, E., & Richardson, M. (2020). Employing models of human social motor behavior for artificial agent trainers. AAMAS 2020, 1134-1142. DOI:doi.org/10.5555/3398761.3398893 [Open Access Version]
  • Raul F.R., Debie, E., Fidock, J., Barlow, M., Merrick, K., Anavatti, S., Garratt, M., & Abbass H.A. (2020). Electroencephalographic Workload Indicators During Teleoperation of an Unmanned Aerial Vehicle Shepherding a Swarm of Unmanned Ground Vehicles in Contested Environments. Frontiers Neuroscience, 14:40. DOI:doi.org/10.3389/fnins.2020.00040 [Open Access Version]
  • Nalepka, P., Lamb, M., Kallen, R. W., Shockley, K., Chemero, A., Saltzman, E., & Richardson, M. J. (2019). Human social motor solutions for human–machine interaction in dynamical task contexts. Proceedings of the National Academy of Sciences, 116(4), 1437-1446. DOI:10.1073/pnas.1813164116 [Open Access]
  • Wade H., and Abbass H.A. (2019). Cyber-Shepherd: A Smartphone-based Game for Human and Autonomous Swarm Control. IEEE Systems, Man, Cybernetics Conference, Bari, Italy. DOI:doi.org/10.1109/SMC.2019.8914378 [Author Version]
  • Nalepka, P., Kallen, R. W., Chemero, A., Saltzman, E., & Richardson, M. J. (2017). Herd those sheep: Emergent multiagent coordination and behavioral-mode switching. Psychological science, 28(5), 630-650. DOI:10.1177/0956797617692107 [Restricted Access]

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