公益游戏中的学习:不确定性和沟通对合作的影响
Nicole Orzan1, Erman Acar2,3, Davide Grossi1,2,4
1Bernoulli Institute for Mathematics, Computer Science and Artificial Intelligence, University of Groningen, 9747 AG Nijenborgh, Groningen, The Netherlands.
Neural computing & applications
|August 4, 2025
概括
当不确定性被共享时,紧急通信可以加强多代理系统中的合作. 然而,如果一些代理人缺乏不确定性,他们可能会利用其他使用学习的沟通策略在社会困境.
科学领域:
- 人工智能的人工智能
- 多代理系统 多代理系统
- 游戏理论 游戏理论
背景情况:
- 新兴通信是多代理系统合作的关键.
- 现实世界的互动涉及不完整的信息和各种激励.
- 以前的研究经常在孤立的合作,竞争或混合动力环境中训练代理人.
研究的目的:
- 研究新兴沟通在不确定性下的社会困境中的作用.
- 探讨当代理人面临不同程度的激励错位和不确定性时,沟通功能是如何运作的.
- 分析沟通在同时,多样化的激励环境中的影响.
主要方法:
- 开发了一个扩展的公共产品游戏来模拟社会困境.
- 训练有素的独立强化学习代理人,跨越场景与错误的激励措施.
- 引入了对代理人的激励调整的不确定性.
- 使代理人能够学习沟通政策.
主要成果:
- 当所有代理人均有相同的不确定性时,出现的沟通会促进群体合作.
- 不对称的不确定性导致剥削:没有不确定性的代理人欺骗不确定的同行.
- 沟通策略根据代理人之间的不确定性分布而适应.
结论:
- 新兴通信对合作的影响取决于不确定性分布.
- 共享的不确定性可以促进合作,而不对称的不确定性可能导致战略欺骗.
- 这项研究强调了多代理系统中沟通,激励和不确定性之间的复杂相互作用.
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