QWeb: Solving Web Navigation Problems using DQN
Last Updated on July 20, 2023 by Editorial Team
Author(s): Sherwin Chen
Originally published on Towards AI.
Simple Introduction to Web Navigation Problems
Photo by Γmile Perron on Unsplash
Model reinforcement learning algorithms have achieved astonishing results in many real-world games, such as Alpha Go and OpenAI Five. In this article, we discuss a closer-to-life application of reinforcement learning, known as web navigation problems, in which an agent learns to navigate the web following some instructions. Specifically, we discuss an algorithm, named QWeb proposed by Gur et al. in ICLR 2019, that leverage DQN to solve web navigation problems.
Albeit there is no mathematical reasoning going on here, I still put many mathematical expressions to illuminate the underlying process. For better readability, you may want… Read the full blog for free on Medium.
Join thousands of data leaders on the AI newsletter. Join over 80,000 subscribers and keep up to date with the latest developments in AI. From research to projects and ideas. If you are building an AI startup, an AI-related product, or a service, we invite you to consider becoming aΒ sponsor.
Published via Towards AI