SOTAVerified

Delta Schema Network in Model-based Reinforcement Learning

2020-06-17Code Available0· sign in to hype

Andrey Gorodetskiy, Alexandra Shlychkova, Aleksandr I. Panov

Code Available — Be the first to reproduce this paper.

Reproduce

Code

Abstract

This work is devoted to unresolved problems of Artificial General Intelligence - the inefficiency of transfer learning. One of the mechanisms that are used to solve this problem in the area of reinforcement learning is a model-based approach. In the paper we are expanding the schema networks method which allows to extract the logical relationships between objects and actions from the environment data. We present algorithms for training a Delta Schema Network (DSN), predicting future states of the environment and planning actions that will lead to positive reward. DSN shows strong performance of transfer learning on the classic Atari game environment.

Tasks

Reproductions