The strategic selection of resources by selfish agents is a classic research direction, with Resource Selection Games and Congestion Games as prominent examples. In these games, agents select available resources and their utility then depends on the number of agents using the same resources. This implies that there is no distinction between the agents, i.e., they are anonymous. We depart from this very general setting by proposing Resource Selection Games with heterogeneous agents that strive for joint resource usage with similar agents. So, instead of the number of other users of a given resource, our model considers agents with different types and the decisive feature is the fraction of same-type agents among the users. More precisely, similarly to Schelling Games, there is a tolerance threshold $\tau \in [0,1]$ which specifies the agents' desired minimum fraction of same-type agents on a resource. Agents strive to select resources where at least a $\tau$-fraction of those resources' users have the same type as themselves. For $\tau=1$, our model generalizes Hedonic Diversity Games with a peak at $1$. For our general model, we consider the existence and quality of equilibria and the complexity of maximizing social welfare. Additionally, we consider a bounded rationality model, where agents can only estimate the utility of a resource, since they only know the fraction of same-type agents on a given resource, but not the exact numbers. Thus, they cannot know the impact a strategy change would have on a target resource. Interestingly, we show that this type of bounded rationality yields favorable game-theoretic properties and specific equilibria closely approximate equilibria of the full knowledge setting.

翻译：自私智能体的战略资源选择是一个经典研究方向，资源选择博弈与拥塞博弈是其中的突出范例。在这些博弈中，智能体选择可用资源，其效用取决于使用相同资源的智能体数量。这意味着智能体之间没有区别，即它们是匿名的。我们通过提出具有异质智能体的资源选择博弈来脱离这一普适设定，该类智能体致力于与相似智能体共同使用资源。因此，我们的模型不再关注给定资源上的其他用户数量，而是考虑具有不同类别的智能体，其决定性特征在于用户中同类智能体的比例。更准确地说，与谢林博弈类似，存在一个容忍阈值 $\tau \in [0,1]$，用于规定智能体期望在资源上达到的同类智能体最低比例。智能体努力选择那些使用者中至少有 $\tau$ 比例与自身类别相同的资源。当 $\tau=1$ 时，我们的模型推广了峰值在 $1$ 的享乐多样性博弈。针对这一通用模型，我们研究了均衡的存在性与质量、以及社会福利最大化的计算复杂度。此外，我们考虑了一种有限理性模型，其中智能体只能估计资源的效用，因为它们仅知道给定资源上同类智能体的比例而非精确数量。因此，它们无法预知策略变更对目标资源产生的影响。有趣的是，我们证明这种有限理性会带来良好的博弈论性质，且特定均衡能紧密逼近完全信息设定下的均衡。