Learning to search collaboratively: how dyads overcome complexity and misaligned incentives in imperfect modular decompositions
通过实验室实验，研究双人团队在各自负责复杂任务的一个模块时，如何通过并行和顺序搜索来协调行动，克服复杂性和激励错位，实现协作搜索。
Abstract We investigate the search processes that dyads engage in when each human agent is responsible for one module of a complex task. Our laboratory experiment manipulates global vs. local incentives and low vs. high cross-modular interdependence. We find that dyads endogenously learn to coordinate their joint search efforts by engaging in parallel and sequential searches that, over time, give rise to coordinated repeated actions. Such collaborative search emerges despite complexity and misaligned incentives, and without a coordinating hierarchy.