We study the lock-in effect in a network of task assignments. Agents have a heterogeneous fitness for solving tasks and can redistribute unfinished tasks to other agents. They learn over time to whom to reassign tasks and preferably choose agents with higher fitness. A lock-in occurs if reassignments can no longer adapt. Agents overwhelmed with tasks then fail, leading to failure cascades. We find that the probability for lock-ins and systemic failures increase with the heterogeneity in fitness values. To study this dependence, we use the Shannon entropy of the network of task assignments. A detailed discussion links our findings to the problem of resilience and observations in social systems.

翻译：我们在一个任务分配网络中研究锁定效应; 代理人在解决任务方面有多种多样的优势,可以将未完成的任务重新分配给其他代理人; 他们随着时间的推移学习向谁重新分配任务,最好选择更健康的代理人; 当重新分配工作无法再适应时会发生锁定效应; 任务过多的代理人会失败,导致级联失败; 我们发现锁定和系统性失败的可能性随着健身价值的异质性而增加; 为了研究这种依赖性, 我们使用任务分配网络的香农封套。 详细讨论将我们的调查结果与社会系统中的复原力和观察问题联系起来。