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Allocating Teams to Tasks: An Anytime Heuristic Competence-Based Approach

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Multi-Agent Systems (EUMAS 2022)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 13442))

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Abstract

Many practical applications often need to form a team of agents to solve a task since no agent alone has the full set of required competencies to complete the task on time. Here we address the problem of distributing individuals in non-overlapping teams, each team in charge of a specific task. We provide the formalisation of the problem, we encode it as a linear program and show how hard it is to solve it. Given this, we propose an anytime heuristic algorithm that yields feasible team allocations that are good enough solutions. Finally, we report the results of an experimental evaluation over the concrete problem of matching teams of students to internship programs in companies.

*Research supported by projects AI4EU (H2020-825619), TAILOR (H2020-952215), 2019DI17, Humane-AI-Net (H2020-952026), Crowd4SDG (H2020-872944), and grant PID2019-104156GB-I00 funded by MCIN/AEI/10.13039/501100011033.

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Notes

  1. 1.

    This work is an extended version of our earlier work presented in [16, 17].

  2. 2.

    Note: we use subscript a to refer to the set of competences and the identifier of an agent \(a\in A\), and subscript \(\tau \) to refer to the elements of task \(\tau \in T\).

  3. 3.

    As noted by [22], recent definitions on the term team refer to the specific subtask/ competences that will be performed by each agent.

  4. 4.

    As noted in [9], the product favours both increases in overall team utility and inequality-reducing distributions of individuals’ contributing values.

  5. 5.

    Note that the NOMTMT allocation problem is interrelated with the |T| optimisation problems. However, for a fixed team allocation, the inner optimisation problems are independent from one another.

  6. 6.

    Notably, the marks applied by the evaluators indicate rankings and therefore these numbers are meaningless; thus we turn to tournaments.

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Authors and Affiliations

  1. Artificial Intelligence Research Institute, CSIC, Barcelona, Spain

    Athina Georgara, Juan A. Rodríguez-Aguilar & Carles Sierra

  2. Enzyme Advising Group, Barcelona, Spain

    Athina Georgara

Authors
  1. Athina Georgara
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  2. Juan A. Rodríguez-Aguilar
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  3. Carles Sierra
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Correspondence to Athina Georgara .

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  1. University of Düsseldorf, Düsseldorf, Germany

    Dorothea Baumeister

  2. University of Düsseldorf, Düsseldorf, Germany

    Jörg Rothe

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Georgara, A., A. Rodríguez-Aguilar, J., Sierra, C. (2022). Allocating Teams to Tasks: An Anytime Heuristic Competence-Based Approach. In: Baumeister, D., Rothe, J. (eds) Multi-Agent Systems. EUMAS 2022. Lecture Notes in Computer Science(), vol 13442. Springer, Cham. https://doi.org/10.1007/978-3-031-20614-6_9

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  • DOI: https://doi.org/10.1007/978-3-031-20614-6_9

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