积极推断与同理心机制对于社会行为的人工代理人在不同的情况
Tadayuki Matsumura1, Kanako Esaki2, Shao Yang2
1Hitachi, Ltd. tadayuki.matsumura.bh@hitachi.com.
Artificial life
|November 29, 2023
概括
这项研究引入了一种新的方法,让人工智能代理人通过将同情心整合到主动推理中来表现出社会行为. 使用这种方法的代理人将他们的行为适应社会背景,在各种场景中表现优于标准方法.
科学领域:
- 人工智能的人工智能
- 机器人技术 机器人技术 机器人技术
- 认知科学 认知科学
背景情况:
- 在人工智能中定义和实现适当的社会行为是具有挑战性的,因为情况的变化.
- 现有的代理控制方法,如标准的积极推断,可能无法充分捕捉微妙的社会相互作用.
研究的目的:
- 提出和评估一种新的方法,让人工智能表现出适应性的社会行为.
- 将同理心融入到积极的推理中,以实现情境意识的社交互动.
主要方法:
- 拟议的方法将同理心融入到主动推理的框架中.
- 该方法通过在各种模拟情况下控制自主移动机器人来评估.
- 在社会适应性方面,与标准主动推理控制对比了代理行为.
主要成果:
- 由拟议的同情主动推理方法控制的代理人表现出比使用标准主动推理的代理人更具适应性的社会行为.
- 在两个代理商的场景中,拟议的方法导致对方代理商的行程距离减少13.7%,代理商间利率增加25.8%.
- 代理商的行为受到周围代理商的社会倾向的调节,与利他主义代理商表现出更多的社会行为,与自私的代理商表现出更少的社会行为.
结论:
- 将同理心纳入主动推理中,为人工智能提供了一个可行的机制,以实现适应性的社会行为.
- 拟议的方法显示了开发更复杂和社会智能的自主系统的前景.
- 未来的工作可以探索不同程度的同情心和不同社会背景对代理行为的影响.
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