Investigating Human Priors for Playing Video Games

Rachit Dubey, Pulkit Agrawal, Deepak Pathak, Thomas L. Griffiths, Alexei A. Efros

Abstract: What makes humans so good at solving seemingly complex video games? Unlike computers, humans bring in a great deal of prior knowledge about the world, enabling efficient decision making. This paper investigates the role of human priors for solving video games. Given a sample game, we conduct a series of ablation studies to quantify the importance of various priors. We do this by modifying the video game environment to systematically mask different types of visual information that could be used by humans as priors. We find that removal of some prior knowledge causes a drastic degradation in the speed with which human players solve the game, e.g. from 2 minutes to over 20 minutes. Furthermore, our results indicate that general priors, such as the importance of objects and visual consistency, are critical for efficient game-play.

TL;DR: We investigate the various kinds of prior knowledge that help human learning and find that general priors about objects play the most critical role in guiding human gameplay.

Keywords: Prior knowledge, Reinforcement learning, Cognitive Science

Community Implementations: [ 3 code implementations](https://www.catalyzex.com/paper/arxiv:1802.10217/code)