Web Agents

Web agents study how AI systems can carry out multi-step tasks on websites, from finding information to filling forms and making purchases. Common approaches combine visual or DOM-based page understanding with planning, action grounding, memory, and reusable skills; training often uses human demonstrations, synthetic environments, or reinforcement learning. Benchmarks such as WebArena, Mind2Web, and WebVoyager measure task success, while live-web tests expose challenges from changing interfaces and complex workflows. A central tension is improving reliability and efficiency without compromising security, privacy, or faithful execution of user intent.