Abstract

Systems and methods are disclosed for automatically identifying and initiating booking operations based on booking availability in online reservation platforms. An artificial intelligence (AI)-driven browser automation system monitors booking platforms/interfaces on websites to detect changes in availability and infer patterns associated with the release of new booking slots. Based on observed changes in availability over time, the system estimates when new availability is likely to become accessible. The system may periodically interact with the booking platform by navigating webpages, submitting forms, retrieving availability information, or analyzing page content. Once a predicted availability release time is determined/predicted, the system schedules and executes an automated booking workflow at or near the predicted time. The automated workflow may include accessing the booking platform, performing required interactions such as authentication or form submission, checking availability, and attempting to secure a reservation on behalf of a user. In some scenarios, monitoring and inference operations may be performed by a centralized system that aggregates observations across multiple devices, or through distributed inference based on aggregated booking attempts. The disclosed approach enables proactive identification of booking opportunities and automated execution of booking actions, thereby improving prediction accuracy, reducing redundant network traffic, reducing manual monitoring and improving the likelihood of securing reservations.

Creative Commons License

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.

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