Competitive Multiagent Systems: Bridging the Gap between Theory and Practice

竞争多智能体系统是两个或多个自利智能体交互的环境。正是这种自利的成分使得多主体系统具有“竞争性”：主体的愿望不能依赖于一致。 博弈论是研究这种环境的主要方法。 不幸的是，理论与实践之间仍然存在着巨大差距。 例如，博弈论模型通常非常小，并且建立在代理无所不知（没有错误信念）和效用最大化（计算无界）的假设之上。 即使这样的代理人确实存在，现有的理论也不会告诉他如何推理更有限的竞争者。 资源分配的方法通常假设供销售的货物不能转售，并且是独特的（即，它们只在设计中的一次性市场中可用），代理人没有交易成本或预算，市场可以在没有任何限制的情况下重新设计，代理人知道他们对所分配货物的估价。 在相关的实际环境中，这些假设中的一些甚至全部可能不成立。

Competitive multiagent systems are environments in which two or more self-interested agents interact. It is this ingredient of self-interest that makes a multiagent system ``competitive": agents' desires cannot be relied upon to coincide. Game theory is the dominant approach used to study such environments. Unfortunately, a significant gap still exists between theory and practice. For example, game-theoretic models are typically very small and are built on the assumptions that agents are omniscient (hold no false beliefs) and utility-maximizing (computationally-unbounded). Even if such an agent did exist, existing theories would not tell him how to reason about more limited competitors. Approaches to resource allocation usually assume that goods for sale cannot be resold and are unique (i.e., they are available only in the one-shot market being designed), that agents face no transaction costs or budgets, that markets can be redesigned without any constraints, and that agents know their valuations for the goods being allocated. In practical settings of interest, some or even all of these assumptions can fail to hold.