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

事实证明，决策论和博弈论在指导决策和战略思考方面非常有用。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将比不遵循博弈论建议的玩家表现差得多。当前理论的这些预测失败源于许多来源，包括：1)当前理论隐含地假设代理人是完美的推理者，他们可以计算他们行为的后果；2)当前的解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代理人知道所有其他代理人在做什么；4)当前的方法没有考虑语言--它们隐含地假设所有玩游戏(或决策)的代理人以相同的方式描述博弈(或决策问题)，并且具有相同的世界理论；5)根据博弈/决策问题的建模者的说法，所有的代理都被假设为理性的，这些观察结果中的大多数都不是新的(在后面的章节中提供了对以前工作的参考)。现在是时候把所有这些观察放在一起，为博弈论和决策论提出更现实的基础了。这个项目的目标是通过使用从逻辑、密码学和稳健分布式计算的广泛技术来构建这样的基础，然后将这些思想应用到稳健机制设计(即做出选择的规则)的问题上。该项目探索了计算机科学和博弈论的新的研究方向，由此产生的综合应该丰富这两个领域。它还应产生更广泛的社会影响，包括更有力地设计拍卖机制；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，使用户更容易理解决策，并更好地考虑到其他用户的行动；更广泛地说，更深入地了解相互作用的代理的行动。

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.