Laboratory for Brain and Machine Intelligence

Laboratory for Brain and Machine Intelligence @ KAIST

Laboratory for brain and machine intelligence, KAIST

Working papers

  1. D. Kim, G. Y. Park, J. P. O’Doherty*, and S. W. Lee*, “Task complexity interacts with state-space uncertainty in the arbitration process between model-based and model-free reinforcement-learning at both behavioral and neural levels,” bioRxiv, 2018. (

  2. S. Heo and S. W. Lee*, “Effects of depression on prefrontal striatal goal directed and habitual control,” bioRxiv, 2018. (

  3. J. Lee, J. D. Kralik, Y. Cha, S. Heo, and S. W. Lee*, “Decoupling between causal understanding and awareness during learning and inference,” bioRxiv, 2018. (

  4. M. R. Song and S. W. Lee*, “How do dopamine neurons resolve a tradeoff between performance and energy?,” bioRxiv, 2018. (

  5. S. Weissengruber (co-first), S. W. Lee (co-first), John P. O'Doherty, Christian C. Ruff, “Neurostimulation reveals context-dependent arbitration between model-based and model-free learning, “ 2018.

  6. S. W. Lee* and B. Seymour*, “Decision-making in brains and robots - the case for an interdisciplinary approach,” 2018.

  7. J. H. Lee+, B. Seymour+*, J. Leibo, S. J. An, S. W. Lee*, “Towards High-Performance, Memory-Efficient, and Fast Reinforcement Learning: Lessons from Decision Neuroscience,” 2018.

  8. D. Kim and S. W. Lee*, “Dynamic encoding of task structure changes in model-based and model-free reinforcement learning,” 2018.

  9. K. Seo, C. Lee, H. Choi, and S. W. Lee*, “Boosting Neural Network Training with Hypothetical Sample Synthesis,” 2018. 

  10. S. Heo, C. H. Lee and S. W. Lee*, “Encoding and decoding hypotheses for highly complex experimental design,” 2018.

  11. S. J. An, B. Martino, S. W. Lee*, “Evidence of human metacognitive exploration in reinforcement learning,” 2018.

  12. J. H. Lee and S. W. Lee*, “Optimal control of human inference processes,” 2018.

Journal publications

  1. Wang, O., Lee, S.W., O’Doherty, J., Seymour, B., and Wako, Y. Model-based and model-free pain avoidance learning. Brain Neurosci. Adv. 2 (2018).

  2. Joo, H., Kim, J., and Lee, S.W.* Model-based reinforcement learning using probabilistic simulation. J. Korean Inst. Intell. Syst. 27, 1–5 (2018). (written in Korean)

  3. Lee, S. W.* Reinforcement learning: from algorithms to neuroscience. Commun. KIISE, 36, 8–16 (2018). (written in Korean)

  4. Choung, O., Lee, S. W.* & Jeong, Y.* Exploring Feature Dimensions to Learn a New Policy in an Uninformed Reinforcement Learning Task. Scientific Reports 7, 17676 (2017).

  5. Lee, S. W.*, Yi, T., Han, J.-S., Jung, J.-W., and Bien, Z. Design of a Gait Phase Recognition System that can cope with EMG Electrode Location Variation. IEEE Transactions on Automation Science and Engineering 14(3) (2017).

  6. An, S. J. & Lee, S. W.* A Study on the Exploration-Exploitation Dilemma using an uncertainty-driven state space learning algorithm. J. Korean Inst. Intell. Syst. 27, (2017). (written in Korean)

  7. Lee, S.W.*, O'Doherty, J.P., and Shimojo, S. Neural computations mediating one-shot learning in the human brain. PLOS Biology 13(4): e1002137 (2015).
    (synopsis "How one-shot learning unfolds in the brain" by Weaver, J.)

  8. O'Doherty, J.P., Lee, S.W., McNamee, D. The structure of reinforcement-learning mechanisms in the human brain. Current Opinion in Behavioral Sciences 1, 94-100 (2015).

  9. Lee, S.W.*, Shimojo, S., and O'Doherty, J.P. Neural computations underlying arbitration between model-based and model-free learning. Neuron 81, 687-699 (2014).
    (front cover; preview "Decisions about decisions" by Yoshida, W. and Seymour, B.)

  10. Lee, S.W.*, Prenzel, O., and Bien, Z. Applying Human Learning Principles to User-Centered IoT Systems. IEEE Computer 46, 46-52 (2013). (cover feature)

  11. Han, J.-S., Lee, S.W.*, and Bien, Z. Feature Subset Selection Using Separability Index Matrix. Information Sciences 223, 102-118 (2013).

  12. Isik, L., Leibo, J.Z., Mutch, J., Lee, S.W., and Poggio, T. A hierarchical model of peripheral vision. MIT CSAIL Technical Report, MIT-CSAIL-TR-2011-031 (2011).

  13. Jeon, M., Lee, S.W., and Bien, Z. Hand Gesture Recognition using Multivariate Fuzzy Decision Tree and User Adaptation. International Journal of Fuzzy System Applications 1, 15-31 (2011).

  14. Bien, Z. and Lee, S.W. Learning Structure of Human Behavior Patterns in a Smart Home System. Advances in Intelligent and Soft Computing 82, 1-15 (2010).

  15. Lee, S.W., Kim, Y.S., and Bien, Z. A Non-Supervised Learning Framework of Human Behavior Patterns Based on Sequential Actions. IEEE Transactions on Knowledge and Data Engineering 22, 479-492 (2010).

  16. Lee, S.W. and Bien, Z. Representation of a Fisher Criterion Function in a Kernel Feature Space. IEEE Transactions on Neural Networks 21, 333-339 (2010).

  17. Lee, S.W., Kim, Y.S., Park, K.-H., and Bien, Z. Iterative Bayesian Fuzzy Clustering toward Flexible Icon-based Assistive Software for the Disabled. Information Sciences 180, 325-340 (2010).

  18. Grigorescu, S.M., Lee, S.W., and Ristic-Durrant, D. Robust Object Recognition in Service Robotics. Proceedings of 30th Colloquium of Automation (2009).

  19. Song, J.-H., Jung, J.-W., Lee, S.W., and Bien, Z. Robust EMG Pattern Recognition to Muscular Fatigue Effect for Powered Wheelchair Control. Journal of Intelligent & Fuzzy Systems 20, 3-12 (2009).

  20. Prenzel, O., Lee, S.W., Bien, Z., and Graeser, A. A Study on the Application of the Software Framework MASSiVE in KAIST's Intelligent Sweet Home System. International Journal of Assistive Robotics and Mechatronics 9 (2008).

  21. Jeon, M., Do, J.-H., Lee, S.W., Park, K.-H., and Bien, Z. A Personalized Hand Gesture Recognition System using Soft Computing Techniques. Journal of Korea Institute of Intelligent Systems 18, 53-59 (2008). (written in Korean)

  22. Bien, Z., Han, J.-S., and Lee, S.W. Feature Subset Selection of Biosignals for Rehabilitation System. Proceedings of 28th Colloquium of Automation (2007).

  23. Kim, S., Jeon, M., Lee, S.W., Park, K.-H., and Bien, Z. Development of Assistive Software for Disabled and Aged People Based on User Characteristics - Unified User Interface for Special Work Chair. Journal of the Institute of Electronics Engineers of Korea 44 (2007). (written in Korean)

  24. Kim, Y.S., Lee, S.W., Kang, S., Baek, Y.S., Hwang, S. and Bien, Z. Supervised IAFC Neural Network Based on the Fuzzi cation of Learning Vector Quantization. Lecture Notes in Computer Science 4253, 248-254 (2006).

  25. Lee, S.W., Kim, D.-J., Kim, Y.S., and Bien, Z. Gabor Wavelet Neural Network-Based Facial Expression Recognition System. Journal of Fuzzy Logic and Intelligent System 16, 1-7 (2006). (written in Korean)

  26. Lee, S.W., Kim, D.-J., Kim, Y.S., and Bien, Z. Training of Feature Extractor via New Cluster Validity - Application to Adaptive Facial Expression Recognition. Lecture Notes in Computer Science 3864, 542-547 (2005).

  27. Kwon, Y.-J., Kim, D.-J., Lee, S.W., and Bien, Z. Development of Half-Mirror Interface System and Its Application for Ubiquitous Environment. Journal of Control, Automation and System Engineering 11, 1-7 (2005). (written in Korean)