# Grading Complex Interactive Coding Programs with Reinforcement Learning

DevFeed: [Grading Complex Interactive Coding Programs with Reinforcement Learning](<https://devfeed.tech/articles/grading-complex-interactive-coding-programs-with-reinforcement-learning-7587.md>)

Original publisher: [Read original article](<https://ai.stanford.edu/blog/play-to-grade/>)

Author: A Href; Allen Nie; Emma Brunskill; Chris Piech

Published: 2022-03-28T07:00:00Z

Content type: article

Language: en

Sources: [The Stanford AI Lab Blog](<https://devfeed.tech/sources/the-stanford-ai-lab-blog.md>)

Topics: [rlvr](<https://devfeed.tech/topics/rlvr.md>), [Code Challenge](<https://devfeed.tech/topics/code-challenge.md>), [Artificial Intelligence](<https://devfeed.tech/topics/ai.md>), [Programming](<https://devfeed.tech/topics/programming.md>), [NeurIPS](<https://devfeed.tech/topics/neurips.md>), [browser](<https://devfeed.tech/topics/browser.md>)

Tags: [agents](<https://devfeed.tech/tags/agents.md>), [algorithms](<https://devfeed.tech/tags/algorithms.md>), [browser](<https://devfeed.tech/tags/browser.md>), [coding](<https://devfeed.tech/tags/coding.md>), [courses](<https://devfeed.tech/tags/courses.md>), [games](<https://devfeed.tech/tags/games.md>), [machine-learning](<https://devfeed.tech/tags/machine-learning.md>), [neurips](<https://devfeed.tech/tags/neurips.md>), [programming](<https://devfeed.tech/tags/programming.md>), [reinforcement-learning](<https://devfeed.tech/tags/reinforcement-learning.md>), [speed](<https://devfeed.tech/tags/speed.md>)

## AI overview

This article presents the Play to Grade Challenge, which applies reinforcement-learning methods for game-playing AI agents to the automated grading of complex interactive coding assignments. It explains why games and interactive applications are difficult to evaluate automatically and describes the challenge introduced in a NeurIPS 2021 paper.

## Source excerpt

[Summary] tl;dr: A tremendous amount of effort has been poured into training AI algorithms to competitively play games that computers have traditionally had trouble with, such as the retro games published by Atari, Go, DotA, and StarCraft II. The practical machine learning knowledge accumulated in developing these algorithms has paved the way for people to now routinely train game-playing AI agents for many games. Following this line of work, we focus on a specific category of games - those developed by students as part of a programming assignment. Can the same algorithms that master Atari games help us grade these game assignments? In our recent NeurIPS 2021 paper, we illustrate the challenges in treating interactive coding assignment grading as game playing and introduce the Play to Grade Challenge. Introduction Massive Online Coding Education has reached striking success over the past decade. Fast internet speed, improved UI design, code editors that are embedded in a browser window allow educational platforms such as Code.org to build a diverse set of courses tailored towards students of different coding experiences and interest levels (for example, Code.org offers "Star War-themed coding challenge," and "Elsa/Frozen themed for-loop writing"). As a non-profit organization, Code.org claims to have reached over 60 million learners across the world 1. Such organizations typically provide a variety of carefully constructed teaching materials such as videos and programming challenges. A challenge faced by these platforms is that of grading assignments. It is well known that grading is critical to student learning 2, in part because it motivates students to complete their assignments. Sometimes manual grading can be feasible in small settings, or automated grading used in simple settings such as when assignments are multiple choice or adopt a fill-in-the-blink modular coding structure. Unfortunately, many of the most exciting assignments, such as developing games or i