Skip to content


For a complete list of my publications, please see my Google scholar.

Recent (2023) and selected other publications:

RoboCup 2021, Rachid Alami, Joydeep Biswas, Maya Cakmak, Oliver Obst (eds)
  • Fabian C Weigend, DC Clarke, O Obst, J Siegler. A hydraulic model outperforms work-balance models for predicting recovery kinetics from intermittent exercise  Annals of Operations Research 325 (1), 589-613
  • Rajvir Kaur, JA Ginige, O Obst. AI-based ICD coding and classification approaches using discharge summaries: A systematic literature review. Expert Systems with Applications 213, 118997
  • Sunpreet Sharma, Gu Fang, Zhong-Hua Chen, Oliver Obst, David Tissue, Ju Jia Zou, Weiguang Liang. Capsicum Flower Identification for Robotic Pollination in Greenhouses. IEEE 2023 International Conference on Machine Learning and Cybernetics (ICMLC).
  • Sayed Waleed Qayyumi, Laurence AF Park, Oliver Obst. Few-Shot and Transfer Learning with Manifold Distributed Datasets. Australasian Conference on Data Science and Machine Learning, 137-149, Springer.
  • Frieder Stolzenburg, Olivia Michael, Oliver Obst. The Power of Linear Recurrent Neural Networks-Predictive Neural Networks
    Preliminary version presented at Cognitive Computing, 2018. Best poster award: Most Technologically Feasible Poster Contribution.
RoboCup 2017, Hidehisa Akiyama, Oliver Obst, Claude Sammut (eds.)
  • Trevor Barron, Oliver Obst, Heni Ben Amor. Information Maximizing Exploration with a Latent Dynamics Model
    Presented at the NIPS 2017 Deep Reinforcement Learning Symposium.
  • Hidehisa Akiyama, Oliver Obst, Claude Sammut, Flavio Tonidandel (editors). RoboCup 2017: Robot World Cup XXI. Springer Lecture Notes in Artificial Intelligence 11175, 2018.  
  • James Arvanitakis, Andrew Francis, Oliver Obst. Data ethics is more than just what we do with data, it’s also about who’s doing it. The Conversation, June 22, 2018.


  • Zeman, A, Obst, O, Brooks, KR & Rich, AN 2013, The Müller-Lyer illusion in a computational model of biological object recognition, Plos One, vol. 8, no. 2, pp. e56126.
  • Hartmann, C, Boedecker, J, Obst, O, Ikemoto, S & Asada, M 2013, Real-Time inverse dynamics learning for musculoskeletal robots based on echo state Gaussian process regression, Robotics: Science and Systems, vol. 8, pp. 113-120
  • Obst, O & Riedmiller, M 2012, Taming the reservoir: Feedforward training for recurrent neural networks, Neural Networks (IJCNN), The 2012 International Joint Conference on, pp. 1–7
  • Boedecker, J, Obst, O, Lizier, JT, Mayer, NM & Asada, M 2012, Information processing in echo state networks at the edge of chaos, Theory in Biosciences, vol. 131, no. 3, pp. 205-213
  • Prokopenko, M, Lizier, JT, Obst, O & Wang, XR 2011, Relating Fisher information to order parameters, Physical Review E - Statistical, Nonlinear, and Soft Matter Physics, vol. 84, no. 4
  • Jurdak, R, Wang, XR, Obst, O & Valencia, P 2011, Wireless Sensor Network Anomalies: Diagnosis and Detection Strategies, Intelligence-Based Systems Engineering, Springer, pp. 309–325
  • Prokopenko, M, Ay, N, Obst, O & Polani, D 2010, Phase transitions in least-effort communications, Journal of Statistical Mechanics: Theory and Experiment, vol. 2010, no. 11, pp. P11025
  • Obst, O, Wang, XR & Prokopenko, M 2008, Using echo state networks for anomaly detection in underground coal mines, Proceedings - 2008 International Conference on Information Processing in Sensor Networks, IPSN 2008, pp. 219-229
  • Ben Amor, H, Murray, J & Obst, O 2006, Fast, Neat and Under Control: Inverse Steering Behaviors for Physical Autonomous Agents, Charles River Media, pp. 221–232
  • Obst, O & Rollmann, M 2005, Spark - A generic simulator for physical multi-agent simulations, Computer Systems Science and Engineering, vol. 20, no. 5, pp. 347-356