ScheduleMe: Multi-Agent Calendar Assistant
Fuente:
arXiv
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| Autori principali: | , , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2025
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| Soggetti: | |
| Accesso online: | |
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| _version_ | 1866911523860905984 |
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| author | Wijerathne, Oshadha Nimasha, Amandi Fernando, Dushan de Silva, Nisansa Perera, Srinath |
| author_facet | Wijerathne, Oshadha Nimasha, Amandi Fernando, Dushan de Silva, Nisansa Perera, Srinath |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2509_25693 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | ScheduleMe: Multi-Agent Calendar Assistant Wijerathne, Oshadha Nimasha, Amandi Fernando, Dushan de Silva, Nisansa Perera, Srinath Artificial Intelligence 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. |
| title | ScheduleMe: Multi-Agent Calendar Assistant |
| topic | Artificial Intelligence |
| url | https://arxiv.org/abs/2509.25693 |