State-Outcome Mappings for Industries
收藏arXiv2025-09-30 收录
下载链接：
https://github.com/RPD123-byte/Demonstrating-the-Continual-Learning-Capabilities-and-Practical-Application-of-Discrete-Time-Active
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资源简介：
该数据集包含了16个不同行业预定义的状态-结果映射，以及各自的研究过程，旨在评估主动推断智能体的持续学习能力。此外，该数据集还用于根据智能体在多次试验中对各种结果的价值信念和置信度来计算其得分。涵盖的行业范围广泛，包含多个研究过程，其任务是在动态环境中进行持续学习和适应。
This dataset contains 16 predefined state-outcome mappings across different industries, along with their respective research procedures, and is designed to evaluate the continual learning capabilities of active inference agents. Furthermore, this dataset is used to compute the scores of agents based on their value beliefs and confidence levels toward various outcomes across multiple trials. Covering a broad range of industries, it encompasses multiple research processes whose tasks involve continual learning and adaptation in dynamic environments.
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