Program
• The movies of lectures (upon approval by the speaker) and discussions are available from Vimeo.
• Registered participants can access all the lecture movies from the Slack channels and post questions and comments.
• Poster sessions, reception, banquet, and round-table are cancelled. You can find the abstracts and optional links to poster and movie files here.
Saturday, October 10 (time in UTC)
- 9:00
- Playback of Keynote lecture and Session 1 talks
- 13:00
- Get connected
- 13:15
- Greeting:
Kenji Doya (Okinawa Institute of Science and Technology) - 13:30
- Discussion on the Keynote lecture:
Josh Tenenbaum (Massachusetts Institute of Technology)
“Building Machines That See, Think and Learn Like People”
- 14:00
- Discussion on Session 1 talks: Deep Learning and Reinforcement Learning
- Chair: Jun Morimoto (ATR Brain Information Communication Research Laboratory Group)
Discussant: Shun-ichi Amari (RIKEN Center for Brain Science)
- Yann LeCun (Facebook AI Research & New York University)
“Self-Supervised Learning” - Yutaka Matsuo (The University of Tokyo)
“World Model for Perception, Control and Language” - Doina Precup (McGill University)
“Fast Reinforcement Learning with Generalized Policy Updates” - David Silver (DeepMind)
“Deep Reinforcement Learning from AlphaGo to AlphaStar” - Masashi Sugiyama (RIKEN Center for Advanced Intelligence Project / The University of Tokyo International Research Center for Neurointelligence)
“Recent Advances in Robust Machine Learning”
Sunday, October 11 (time in UTC)
- 6:30
- Playback of Session 2 & 3 talks
- 13:00
- Discussion on Session 2 talks: World Model Learning and Inference
- Chair: Hiroaki Gomi (NTT Communication Science Laboratories)
Discussant: Mitsuo Kawato (ATR)
- Ila Fiete (Massachusetts Institute of Technology)
“Mixed Modular Codes and Remapping for Highly Generalizable Learning and Inference” - Karl Friston (University College London)
“Active Inference and Artificial Curiosity” - Yukie Nagai (The University of Tokyo International Research Center for Neurointelligence)
“Cognitive Development Based on Predictive Coding” - Maneesh Sahani (Gatsby Computational Neuroscience Unit)
“How Do Neural Systems Learn to Infer?” - Tadahiro Taniguchi (Ritsumeikan University)
“Symbol Emergence in Robotics: Pursuing Integrative Cognitive Architecture Using Probabilistic Generative Models for Real-world Language Acquisition”
- 14:00
- Discussion on Session 3 talks: Metacognition and Metalearning
- Chair: Masayuki Matsumoto (University of Tsukuba)
Discussant: Keiji Tanaka (RIKEN Center for Brain Science)
- Matthew Botvinick (DeepMind)
“Object-oriented deep learning” - Ryota Kanai (ARAYA Inc.)
“Consciousness and Intelligence” - Angela Langdon (Princeton University)
“Model-based Reward Prediction: Algorithms for Learning to Represent a Task” - Hiroyuki Nakahara (RIKEN Center for Brain Science)
“Neural Computations for Making Decisions with Others’ Rewards and Decisions” - Xiao-Jing Wang (New York University)
“Learning to Learn and the Brain”
Monday, October 12 (time in UTC)
- 6:30
- Playback of Session 4 & 5 talks
- 13:00
- Discussion on Session 4 talks: AI for Neuroscience and Neuromorphic Technologies
- Chair: Takatoshi Hikida (Osaka University)
Discussant: Kunihiko Fukushimas (FLSI)
- James J. DiCarlo (Massachusetts Institute of Technology)
“Reverse Engineering Visual Intelligence” - Yukiyasu Kamitani (Kyoto University)
“Reconstructing Visual and Subjective Experience from the Brain” - Rosalyn Moran (King’s College London)
“The Free Energy Principle and Active Inference in Silico and in Vivo, Visual Sampling and ‘World Model’ Building” - Terrence Sejnowski (Salk Institute & Univesity of California San Diego)
“Artificial Intelligence Meets Human Intelligence” - Hidehiko Takahashi (Tokyo Medical and Dental University)
“Interface between AI and Psychiatry Research”
- 14:00
- Discussion on Session 5 talks: Social Impact and Neuro-AI Ethics
- Chair: Masamichi Sakagami (Tamagawa University)
- Anne Churchland (University of California, Los Angeles)
“Single-trial Neural Dynamics Are Dominated by Richly Varied Movements” - Kenji Doya (Okinawa Institute of Science and Technology)
“Toward the Society of AI Agents: What Should We Learn from the Brain and Human Society” - Arisa Ema (The University of Tokyo Institute for Future Initiatives)
“‘Interpretative Flexibility’ in AI and Neuroscience Research” - Hiroaki Kitano (Okinawa Institute of Science and Technology)
“Nobel Turing Challenge: A Grand Challenge on AI for Scientific Discovery” - Stuart Russell (University of California, Berkeley)
1. “Brains, Circuits, and Things”
2. “Human Compatible Artificial Intelligence”