We consider the problem of forming collectives of agents inherent in application domains aligned with Sustainable Development Goals 4 and 11 (i.e., team formation and ridesharing, respectively). We propose a general solution approach based on a novel combination of an attention model and an integer linear program (ILP). In more detail, we propose an attention encoder-decoder model that transforms a collective formation instance to a weighted set packing problem, which is then solved by an ILP. Results on collective formation problems inherent in the ridesharing and team formation domains show that our approach provides comparable solutions (in terms of quality) to the ones produced by state-of-the-art approaches specific to each domain. Moreover, our solution outperforms the most recent general approach for forming collectives based on Monte Carlo tree search.

我们考虑形成与可持续发展目标4 和 11一致的应用领域固有的代理集体的问题（分别是团队组建和乘车共享）。我们提出了一种基于注意力模型和整数线性程序（ILP）的新颖组合的通用解决方案。更详细地说，我们提出了一种注意力编码器-解码器模型，它将集体形成实例转换为加权集打包问题，然后通过 ILP 来解决。关于拼车和团队形成领域固有的集体形成问题的结果表明，我们的方法提供了与每个领域特定的最先进方法产生的解决方案相当的解决方案（在质量方面）。此外，我们的解决方案优于基于蒙特卡罗树搜索形成集体的最新通用方法。