Game-Theorectic Foundation for Multi-Agent Systems

功利主义推理是多智能体系统中一个新兴的研究领域。该奖项支持的研究是在这一领域，虽然它将利用更经典的概念，以及符号推理。这个项目将探讨如何非合作博弈论的工具和方法可以有效地应用于模拟人工计算机为基础的代理人的相互作用。由于这种代理必须编程，研究必须提供明确的模型，代理如何推理的解决方案，这是一个任务，从来没有在传统的博弈论解决。博弈论必须补充一些表述，在这些表述中，可以定义代理人的行动、参考和理性，以及允许代理人计算其决策问题的解决方案的机械程序。这个项目的目的是将代理视为简单的推理机，可以从一组公理和推理规则中获得解决方案。 由于代理人可能会反复互动，因此可能有机会从他们的环境中学习，我们需要为他们提供信念修正工具，并将这些工具嵌入到可行的计算程序中。本研究的结果将为研究多智能体系统中如何实现合作与协调奠定基础。

Utilitarian reasoning has been an area of emerging interest in multi-agent systems. The research supported by this award is in this area, though it will make use of more classical concepts of symbolic reasoning as well. This project will investigate how non-cooperative game-theoretic tools and methods can be usefully applied to model the interactions of artificial computer-based agents. Since such agents must be programmed, the research must provide explicit models of how agents reason to a solution, a task which has never been addressed in traditional game theory. Game theory must be supplemented with representations in which actions, references, and rationality for agents can be defined, as well as with mechanical procedures that allow agents to compute solutions to their decision problems. This project aims to view agents as simple inferential machines that can derive a solution from a set of axioms and inference rules. Since agents may repeatedly interact, and thus may have a chance to learn from their environments, we need to provide them with belief revision tools and embed such tools into viable computational procedures. The results of this research will form basis for studying how cooperation and coordination can be attained in multi-agent systems.