ScheduleMe: Multi-Agent Calendar Assistant
This work addresses the need for more usable and flexible personal calendar assistant tools for users, though it appears incremental as it builds on existing LLM advancements and agent-based systems.
The paper tackles the problem of managing Google Calendar events through natural language by introducing ScheduleMe, a multi-agent calendar assistant that uses a graph-structured coordination mechanism with a central supervisory agent and specialized task agents, resulting in improved modularity, conflict resolution, and context-aware interactions.
Recent advancements in LLMs have contributed to the rise of advanced conversational assistants that can assist with user needs through natural language conversation. This paper presents a ScheduleMe, a multi-agent calendar assistant for users to manage google calendar events in natural language. The system uses a graph-structured coordination mechanism where a central supervisory agent supervises specialized task agents, allowing modularity, conflicts resolution, and context-aware interactions to resolve ambiguities and evaluate user commands. This approach sets an example of how structured reasoning and agent cooperation might convince operators to increase the usability and flexibility of personal calendar assistant tools.