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OpenTalks.AI - Сергей Шумский, Символьное мышление роботов

OpenTalks.AI
February 14, 2019

OpenTalks.AI - Сергей Шумский, Символьное мышление роботов

OpenTalks.AI

February 14, 2019
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  1. Agenda I. Problem Deep Reinforcement Learning II. Solution Deep Symbolic

    Learning III. Prospects Robot Operating System
  2. AlphaZero: intuition + calculation ▪ Deep intuition: Yes ▪ Deep

    planning: No ▪ Complexity of learning ∝ 2 , 3 TFLOPSyears – weights update 500 TFLOPSyears – search options
  3. Google DeepMind research program "One way you can think about

    our research program is: 'Can we build out from our perception, using deep-learning systems and learning from first principles? Can we build out all the way to high-level thinking and symbolic thinking?' " D. Hassabis (Google DeepMind)
  4. Deep symbolic learning ▪ Hierarchy of plans state sequences ▪

    Planning and Learning in real time ▪ Complexity of learning ∝ ∝
  5. Images and Symbols Coding Decoding Image ~ 106 bits Sensors

     States  Actions  Effectors Image ~ 106 bits Symbols ~ 5 bits Planning
  6. The trick: symbolic coding of images 2106 ~ , →

    1 2 … > ( = 30, k = 7)  symbols  images  = 210 <
  7. Symbolic thinking ~ planning ▪ Coding of sequences ~ k

    variants (words) ~ 30 Symbolic sequences can be remembered symbol +1 +2 ~ 30 ~ 30
  8. Deep symbolic learning ▪ Learning useful patterns of interaction with

    the world ▪ At all hierarchical levels ▪ In real time Encoder- Decoder +1 +1 Parser +1 Encoder- Decoder Parser symbols patterns symbols
  9. Agenda I. Problem Deep Reinforcement Learning II. Solution Deep Symbolic

    Learning III. Prospects Robot Operating System
  10. Prospects Sensory intelligence Strategic intelligence Robotic intelligence   Goal

    setting and planning to achieve them Achieving the goal