In multi-objective multi-agent systems (MOMASs), agents explicitly consider the possible trade-offs between conflicting objective functions. We argue that compromises between competing objectives in MOMAS should be analyzed on the basis of the utility that these compromises have for the users of a system, where an agent’s utility function maps their payoff vectors to scalar utility values. This utility-based approach naturally leads to two different optimization criteria for agents in a MOMAS: expected scalarized returns (ESRs) and scalarized expected returns (SERs). In this article, we explore the differences between these two criteria using the framework of multi-objective normal-form games (MONFGs). We demonstrate that the choice of optimization criterion (ESR or SER) can radically alter the set of equilibria in a MONFG when nonlinear utility functions are used.

中文翻译：

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基于效用的多目标范式博弈均衡分析

在多目标多代理系统 (MOMAS) 中，代理明确考虑冲突目标函数之间可能的权衡。我们认为，MOMAS 中竞争目标之间的妥协应该基于这些妥协对系统用户的效用进行分析，其中代理的效用函数将其支付向量映射到标量效用值。这种基于效用的方法自然会导致 MOMAS 中的代理有两种不同的优化标准：预期标化回报 (ESR) 和标化预期回报 (SER)。在本文中，我们使用多目标范式博弈 (MONFGs) 框架探索这两个标准之间的差异。