RI-Small: Robust Game Theory and Decision Theory with Resource-Bounded Agents

决策理论和博弈论已被证明是非常有用的指导决策和战略思维。然而，人们经常以可预测和系统的方式行事，这与决策理论的效用最大化模型不一致。此外，遵循博弈论建议的玩家比不遵循博弈论建议的玩家表现更差。当前理论的这些预测失败有很多原因，包括：1)当前理论隐含地假设智能体是完美的推理者，他们可以计算自己行为的后果；2)目前的解决方案概念假设计算是免费的，因此没有考虑计算成本；3)均衡概念隐含地假设主体知道所有其他主体在做什么；4)当前的方法没有考虑语言——它们隐含地假设所有参与游戏（或做出决策）的智能体都以相同的方式描述游戏（或决策问题），并且拥有相同的世界理论；5)根据博弈/决策问题的建模者，假设所有代理都是理性的。这些观察结果中的大多数都不是新的（在后面的部分中提供了对以前工作的参考）。现在是时候把所有这些观察结果结合起来，为博弈论和决策理论提供更现实的基础了。这个项目的目标是通过使用逻辑、密码学和健壮的分布式计算等广泛的技术来构建这样一个基础，然后将这些思想应用于健壮机制设计（即做出选择的规则）的问题。该项目探索了计算机科学和博弈论的新研究方向，最终的综合将丰富这两个领域。它还应该具有更广泛的社会影响，包括更健全的拍卖机制设计；更好地设计点对点网络；更安全的无线网络；更好的软件代理，让用户更容易理解决策，更好地考虑其他用户的行为；更一般地说，是对相互作用的主体的行为有更深的理解。

Decision theory and game theory have proved to be remarkably useful as guides to decision making and strategic thinking. However, people often behave in predictable and systematic ways that are inconsistent with utility maximization models of decision theory. Moreover, players who follow the recommendations of game theory will do far worse than those who do not. These predictive failures of current theories stem from a number of sources, including:1) current theories implicitly assume that agents are perfect reasoners, who can compute the consequences of their actions;2) current solution concepts assume that computation is free, so do not take into account the cost of computation;3) equilibrium concepts implicitly assume that agents know what all other agents are doing;4) current approaches do not take language into account - they implicitly assume that all agents playing a game (or making a decision) describe the game (or decision problem) the same way, and have the same theory of the world;5) all agents are assumed to be rational, according to the modeler of the game/decision problem.Most of these observations are not new (references to previous work are provided in later sections). The time is now ripe to put all these observations together and come up with more realistic foundations for game theory and decision theory. The goal of this project is to construct such a foundation, by using a broad range of techniques from logic, cryptography, and robust distributed computing, and then apply the ideas to the problem of robust mechanism design (i.e., rules for making choices).The project explores new research directions in both computer science and game theory, and the resulting synthesis should enrich both fields. It should have a broader societal impact as well, including more robust design of mechanisms for auctions; better design of peer-to-peer networks; more secure wireless networks; better software agents, that make decisions more comprehensible to users and that take into better account the actions of other users; and, more generally, a deeper understanding of the actions of interacting agents.