ScriptWorld: A Scripts-based RL Environment

Abhinav Joshi, areeb ahmad, Umang Pandey, Ashutosh Modi

Keywords: language-instructed agents, novel environment, NLU

TL;DR: We propose a new text based environment to teach commonsense knowledge about the world

Abstract: Text-based games provide a framework for developing natural language understanding and commonsense knowledge about the world in reinforcement learning algorithms. Existing text-based environments often rely on fictional situations and characters to create a gaming framework and are far from real-world scenarios. In this paper, we introduce ScriptWorld: A text-based environment for teaching agents about real-world daily chores, imparting commonsense knowledge. To the best of our knowledge, it is the first interactive text-based gaming framework that considers data written by humans (scripts datasets) to create procedural games for daily real-world human activities. We provide gaming environments for 10 daily activities and perform a detailed analysis to capture the richness of the proposed environment. We also test the developed environment using human gameplay experiments and reinforcement learning algorithms as baselines. Our experiments show that the flexibility of the proposed environment makes it a suitable testbed for reinforcement learning algorithms to learn the underlying procedural knowledge in daily human chores.