Title   name
2017 KAIST Math. Colloquium
  Speaker   Krešimir Josic  
  Date 2017-11-02
  Place KAIST
  File  의 1 번째 Real Media 동영상입니다.
Abstract : In a constantly changing world, animals must account for fluctuations and changes in their environment when making decisions. They must make use of recent information, and appropriately discount older, irrelevant information. But to do so they need to learn the rate at which the environment changes. Recent experimental studies show that humans and other animals can indeed do so. However it it is unclear what underlying computations they use to achieve this. Developing normative models of evidence accumulation is a first step in quantifying such decision-making processes. While optimal, these algorithms are computationally intensive. To address this problem we developed an approximation of the normative inference process, and show how this approximate computation can be implemented in neural circuits. In the second part of the talk I will discuss evidence accumulation on networks where private information can be shared between neighboring nodes.