关于老鼠和机器人:一种相互学习范式
Oguzcan Nas1, Defne Albayrak1, Gunes Unal1
1Behavioral Neuroscience Laboratory, Department of Psychology, Boğaziçi University, Istanbul, Turkey.
Journal of the experimental analysis of behavior
|March 12, 2025
概括
这项研究引入了一个新的相互学习系统,动物和机器人相互训练. 这种双向的方法允许双方通过奖励或惩罚信号来适应和实现目标.
科学领域:
- 机器人技术 机器人技术 机器人技术
- 人工智能的人工智能
- 动物行为 动物行为
背景情况:
- 传统的动物训练和人工智能研究往往涉及单向学习.
- 现有的范式缺乏生物和人工剂之间的相互适应.
研究的目的:
- 开发和验证一种新的动物机器人交互模式,用于双向学习.
- 为了使Wistar老鼠和机器人之间实现动态的,以目标为导向的合作.
主要方法:
- 实施了相互学习框架,其中代理人提供积极/消极反.
- 使用人工增强学习剂在 silico 中测试了这个范式.
- 在实体中验证了系统,使用老鼠-机器人对在操作条件任务中进行验证.
主要成果:
- 人工代理和Wistar老鼠都表现出相互学习,适应行为以最大化奖励.
- 鼠很快就学会了奖励相关的行为,并表现出避免学习.
- 该系统有效地促进了基于合作伙伴反的适应性互动.
结论:
- 开发的范式使动物和机器人之间有效的双向学习成为可能.
- 这一框架促进了动物机器相互作用研究和学习规则的研究.
- 提供了一个多功能平台,用于在不同的环境中探索合作智能.
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