Jun Tani

Photo of Jun Tani
Jun Tani
Professor
Dr. Eng. (Sophia University Tokyo)
MSc (University of Michigan, Ann Arbor, USA)
BSc (Waseda University, Tokyo)
tani1216jp at gmail.com
Japan
 

  

Experience

  • Sony Computer Science Laboratories Inc., Tokyo, Japan
  • Riken Brain Science Institute, Saitama, Japan
  • Korean Advanced Institute of Science and Technology (KAIST), Daejeon, Korea

News

Selected Publications

Books

Representative Journal Articles

  • Ahmadi, A., & Tani, J. (2019). A Novel Predictive-Coding-Inspired Variational RNN Model for Online Prediction and Recognition. Neural Computation, 31, 2025–2074.
  • Choi, M., & Tani, J. (2017). Predictive Coding for Dynamic Visual Processing: Development of Functional Hierarchy in a Multiple Spatio-Temporal Scales RNN Model. accepted in Neural Computation.
  • Murata, S., Yamashita, Y., Arie, H., Ogata, T., Sugano, S., & Tani, J. (2015). Learning to perceive the world as probabilistic or deterministic via interaction with others: a neuro-robotics experiment. IEEE Transactions on Neural Networks and Learning Systems, (4), 830-848. DOI: 10.1109/TNNLS.2015.2492140
  • Tani, J. (2014). Self-Organization and Compositionality in Cognitive Brains: A Neuro-Robotics Study. Proceedings of the IEEE, Special Issue on Cognitive Dynamic Systems, 102(4), 586-605.
  • Namikawa, J., Nishimoto, R., & Tani, J.(2011). A neurodynamic account of spontaneous behaviour”, PLoS Computational Biology, Vol. 7, Issue 10, e1002221.
  • Yamashita, Y., & Tani, J. (2008). Emergence of functional hierarchy in a multiple timescale neural network model: a humanoid robot experiment. PLoS Computational Biology, Vol.4, Issue.11, e1000220.
  • Sugita, Y., & Tani, J. (2005). Learning semantic combinatoriality from the interaction between linguistic and behavioral processes. Adaptive Behavior, 13(1), 33-52.
  • Tani, J., Ito, M., & Sugita, Y. (2004). Self-organization of distributedly represented multiple behavior schemata in a mirror system: Reviews of robot experiments using RNNPB. Neural Networks, 17, 1273-1289.
  • Tani, J., & Nolfi, S. (1999). Learning to perceive the world as articulated: an approach for hierarchical learning in sensory-motor systems. Neural Networks, 12, 1131-1141.
  • Tani, J. (1998). An interpretation of the ‘Self’ from the dynamical systems perspective: a constructivist approach. Journal of Consciousness Studies, 5(5/6), 516-542.
  • Tani, J. (1996). Model-based learning for mobile robot navigation from the dynamical systems perspective. IEEE Trans. on Syst. Man and Cybern. Part B-Cybernetics, 26(3), 421-436.
  • Tani, J., & Fukumura, N. (1995). Embedding a grammatical description in deterministic chaos: an experiment in recurrent neural learning. Biological Cybernetics, 72, 365-370.

Lecture video: https://www.youtube.com/watch?v=lKIZdP5WnlE

Recent Lectures

  • Invited talk, Tani, J. Mind & Life Europe summer research institute 2020, 'Grounding Knowledge in Uncertainty’, Aug.10 -15, 2020. Video
  • Keynote talk, Tani, J. Cognitive Neurorobotics Study Using Predictive Coding and Active Inference Framework. icra2020 rain PIL Workshop – virtual, New advances in brain-inspired perception, interaction and learning, May 31, 2020.
  • Invited talk, Tani, J. A Proposal of a Novel Variational Bayes Recurrent Neural Network Model Under Predictive Coding and Active Inference Frameworks. Consciousness Club Tokyo, Tokyo, Japan, February 7, 2020. Video
  • Invited talk, Tani, J. Cognitive Neurorobotics Study Using Frameworks of Predictive Coding and Active Inference. BMW Group, Munich, Germany, December 17, 2019.
  • Invited talk, Institute for Cognitive Systems Technische Universität München, Munich, Germany, December 18, 2019.
  • Invited talk, Tani, J. Actions, Symbols and Selves as Self-Organizing Dynamic Phenomena: a View from Neurorobotics study. CHAIN INTERNATIONAL SYMPOSIUM Adventures in Consciousness Science: Exploring the Crossover between Philosophy, Neuroscience, AI, and Robotics, Sapporo, Japan, November 10, 2019.
  • Invited talk, Tani, J. An account of the development of cognitive minds using predictive coding and active inference frameworks. ATR Brain Information Communication Research Laboratory Group Symposium, Kyoto, Japan, October 30, 2019.
  • Keynote talk, Tani, J. Accounting social cognitive mechanisms by the framework of predictive coding and active inference: a synthetic experimental study using robotics interaction platforms. 7th International Conference on Human-Agent Interaction (HAI2019), Kyoto, Japan, October 8, 2019.
  • Invited talk, Tani, J. Emergence in Neurorobotics Experimental Studies. Riken Robotics Retreat, Kyoto, Japan, September 13, 2019.
  • Invited talk, Tani, J. ロボット構成論的アプローチで考える身体的自己と物語的自己について, 第19回Kフォーラム, Takayama, Japan, August 23, 2019.
  • Invited talk, Tani, J. How can compositionality develop through self-exploration and supervised tutoring? Fourth International Workshop on Intrinsically-Motivated Open-ended Learning (IMOL2019), Frankfurt, Germany, July 1-3, 2019.
  • Invited talk, Tani, J. Generating goal-directed planning images using frameworks of predictive coding and active inference: Agency and object constancy. NII Shonam Meeting, Language as Goal-Directed Sequential Behavior: Computational Theories, Brain Mechanisms, Evolutionary Roots, Shonan, Japan, May 21, 2019.
  • Invited talk, Tani, J. Accounts of the development of embodied cognition using predictive coding and active inference frameworks. Marcus Wallenberg International Symposium on Affective and Developmental Processes in Cognitive and Autonomous Systems - Augmenting Deep Learning using Neural Dynamics and Predictive Coding, Gothenburg, Sweden, May 6, 2019.