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#3

Value coding & prediction in the brain

Information

Sep.14th MON 7 - 9 PM ​

@KAIST, N1, Room #111

  • Moderator

: Jineun Kim 

  • Presenter

: Jineun Kim, Jungjoon Park, MinRyung Song

  Contact : kje2436@gmail.com

Agenda

: How do the Brain & AI represent the value? ​​​

1. Values in the agent-environment interaction of BNN & ANN

  • Innate valence encoding in the BNN 

  • Reinforcement Learning (RL) - The unified framework for acquired value representation : Psychological / Neural / Computational perspectives 

  • Neural Correlates of value and prediction error in RL models

  • Can the standard RL fully account for the biological brain?

2. Pannel Discussion​

  • Standard RL vs Homeostatic RL 

  • Further on Model-Free vs Model-Based? 

  • Maladaptive functions of RL framework in patients?

Abstract

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Seminar video

00:00 Introduction & Innate Valence encoding in the Brain / Biological Neural Net (BNN)

24:59 Reinforcement Learning (RL) Framework: Psychology / Machine Learning (ML)

1:02:45 Q&A

1:20:05 Neural correlates of value and prediction error (PE) in RL models

1:43:03 Can the standard RL fully account for the biological brain?

Seminar Slide

Key Materials 

   1) "Reinforcement learning in artificial and biological systems" Neftci & Averbeck. Review_ Nature Machine Intelligence. (2019)

  2) "Where Does Value Come From?" Juechems & Summerfield. Review_Cell (2019)

 3) You can find more key materials here

 

Suggested Pre-Readings/video 

 1) Ch.1_"Reinforcement Learning" by Sutton. 

 2) David Silver's lecture on the Ch1. RL : here  

Pre - Seminar survey

Post - Seminar survey

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Freeboard

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