Neural Episodic Control

Code

• github.com/mjacar/pytorch-nec
  pytorch★ 0
• github.com/hiwonjoon/nec
  tf★ 0
• github.com/Kaixhin/EC
  pytorch★ 0
• github.com/yoojungsun0/Psych239
  pytorch★ 0

Abstract

Deep reinforcement learning methods attain super-human performance in a wide range of environments. Such methods are grossly inefficient, often taking orders of magnitudes more data than humans to achieve reasonable performance. We propose Neural Episodic Control: a deep reinforcement learning agent that is able to rapidly assimilate new experiences and act upon them. Our agent uses a semi-tabular representation of the value function: a buffer of past experience containing slowly changing state representations and rapidly updated estimates of the value function. We show across a wide range of environments that our agent learns significantly faster than other state-of-the-art, general purpose deep reinforcement learning agents.

Tasks

Reproductions