JSAI2024

Presentation information

Organized Session

Organized Session » OS-20

[2K5-OS-20a] OS-20

Wed. May 29, 2024 3:30 PM - 5:10 PM Room K (Room 44)

オーガナイザ:栗原 聡(慶應義塾大学)、山川 宏(東京大学)、谷口 彰(立命館大学)、田和辻 可昌(早稲田大学)

3:50 PM - 4:10 PM

[2K5-OS-20a-02] Proposal for Homeostatic Meta-Planning Method based Large Language Models

Reo Kobayashi1, 〇Reo Abe1, Akifumi Ito2, Kazuma Arii2, Satoshi Kurihara2 (1. Keio University, 2. Keio University )

Keywords:Meta-Planning, Large Language Models, Autonomous Agent

The field of autonomous agent research is rapidly evolving, and there is an increasing need for these agents to be capable of planning in complex environments in a manner akin to humans. Humans have the ability to choose objectives while adapting to their environment, and replicating this process is a key aspect of autonomous agent research. In this study, we propose Homeostatic Meta-Planning Method based Large Language Model to achieve this capability. This method not only shows adaptability in response to environmental changes but also dynamically adjusts the agents' desire values. This enables the selection of objectives while maintaining a balance between desire values and homeostasis. The experimental results validate that this approach effectively facilitates autonomous objective selection based on desires.

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