An attention model for the formation of collectives in real-world domains

• URL: http://arxiv.org/abs/2205.00215v1
• Date: Sat, 30 Apr 2022 09:15:36 GMT
• Title: An attention model for the formation of collectives in real-world domains
• Authors: Adri\`a Fenoy, Filippo Bistaffa, Alessandro Farinelli
• Abstract summary: We consider the problem of forming collectives of agents for real-world applications aligned with Sustainable Development Goals. We propose a general approach for the formation of collectives based on a novel combination of an attention model and an integer linear program.
• Score: 78.1526027174326
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: We consider the problem of forming collectives of agents for real-world applications aligned with Sustainable Development Goals (e.g., shared mobility, cooperative learning). We propose a general approach for the formation of collectives 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 two real-world domains (i.e., ridesharing and team formation for cooperative learning) show that our approach provides solutions that are comparable (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.

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