RI: Medium: Collaborative Research: Game Theory Pragmatics

RI：媒介：协作研究：博弈论语用学

• 批准号: 0963478
• 负责人: Yoav Shoham
• 金额: $ 59.03万
• 依托单位: Stanford University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-07-15 至 2014-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0963478&HistoricalAwards=false
• 关键词: RI; Medium; Collaborative; Research; Game

The past decade has seen unprecedented interaction between artificial intelligence and game theory, with exciting intellectual problems, technical results, and potentially important applications. However, this thriving interaction has thus far not challenged in a fundamental way some of the basic assumptions of game theory, to include various forms of equilibrium as the fundamental strategic concept. Equilibrium specifies conditions under which the strategic choices of agents are in some sense stable. Equilibria are clever and beautiful constructs, but they embody strong idealized assumptions and as a result their applicability to complex, realistic games (i.e., formalizable 'social' interactions) is limited. Arguably computer science can provide alternative modeling foundations, or at least significantly contribute to them. This project explores several complementary directions, to include: alternatives to equilibrium as game solution criteria; replacing analysis of large, complex games with analysis of their abbreviated or approximate versions; using machine-learning techniques to model the extent to which agent behavior is strategic, adaptive, or otherwise intelligent; investigating the role of strategic reasoning in controlled but rich environments, such as Computational Billiards, which involves continuous state and actions spaces as well as control uncertainty. One of the outreach and educational components of this project is organizing and participating in an annual Computational Billiards competition. Applications range from electronic commerce to social networks to peer-to-peer systems to online games, and in general all settings in which individual interests intertwine with computational elements.

在过去的十年里，人工智能和博弈论之间出现了前所未有的互动，出现了令人兴奋的智力问题、技术成果和潜在的重要应用。然而，这种蓬勃发展的互动到目前为止还没有从根本上挑战博弈论的一些基本假设，即将各种形式的均衡作为基本的战略概念。均衡规定了代理人的战略选择在某种意义上是稳定的条件。均衡是聪明而美丽的结构，但它们包含了强烈的理想化假设，因此它们在复杂、现实的游戏(即可形式化的“社会”互动)中的适用性是有限的。可以说，计算机科学可以提供替代的建模基础，或者至少对它们做出重大贡献。这个项目探索了几个互补的方向，包括：作为游戏解决方案标准的均衡的替代方案；用对其缩写或近似版本的分析取代对大型复杂游戏的分析；使用机器学习技术对代理行为具有战略性、适应性或其他智能的程度进行建模；调查战略推理在受控但丰富的环境中的作用，例如计算台球，它涉及连续的状态和动作空间以及控制不确定性。该项目的外展和教育部分之一是组织和参加一年一度的计算台球比赛。应用范围从电子商务到社交网络，从点对点系统到在线游戏，以及总体上个人兴趣与计算元素交织在一起的所有环境。