Deep Reinforcement Learning In Large Discrete Action Spaces. To a degree, linear programs may efficiently solve such large decision problems. Pytorch implementation of the paper "deep reinforcement learning in large discrete action spaces"

The problem is, what reinforcement learning algorithm to use, when we choose only one item from n. Implementation of the algorithm in python 3, tensorflow and openai gym. Being able to reason in an environment with a large number of discrete actions is essential to bringing reinforcement learning to a larger class of problems.

The Problem Is, What Reinforcement Learning Algorithm To Use, When We Choose Only One Item From N.

To a degree, linear programs may efficiently solve such large decision problems. Implementation of the algorithm in python 3, tensorflow and openai gym. And the one choice affect the whole sampled sequence in the next.

Being Able To Reason In An Environment With A Large Number Of Discrete Actions Is Essential To Bringing Reinforcement Learning To A Larger Class Of Problems.

Being able to reason in an environment with a large number of discrete actions is essential to bringing reinforcement learning to a larger class of problems. Pytorch implementation of the paper "deep reinforcement learning in large discrete action spaces"