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STRATA: unified framework for task assignments in large teams of heterogeneous agents

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Abstract

Large teams of heterogeneous agents have the potential to solve complex multi-task problems that are intractable for a single agent working independently. However, solving complex multi-task problems requires leveraging the relative strengths of the different kinds of agents in the team. We present Stochastic TRAit-based Task Assignment (STRATA), a unified framework that models large teams of heterogeneous agents and performs effective task assignments. Specifically, given information on which traits (capabilities) are required for various tasks, STRATA computes the assignments of agents to tasks such that the trait requirements are achieved. Inspired by prior work in robot swarms and biodiversity, we categorize agents into different species (groups) based on their traits. We model each trait as a continuous variable and differentiate between traits that can and cannot be aggregated from different agents. STRATA is capable of reasoning about both species-level and agent-level variability in traits. Further, we define measures of diversity for any given team based on the team’s continuous-space trait model. We illustrate the necessity and effectiveness of STRATA using detailed experiments based in simulation and in a capture-the-flag game environment.

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Notes

  1. Similar to prior work in multi-robot systems [28], we use the term “species” to describe a group of agents with similar traits. This does not imply any similarity to biological species.

  2. We drop the arguments of \(\mathrm {Var}_Y\) for brevity.

  3. Source code acquired from https://github.com/amandaprorok/diversity.git.

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Acknowledgements

We would like to thank the anonymous reviews for their constructive feedback that greatly helped improve the quality of this article. This work was supported by the Army Research Lab under Grant W911NF-17-2-0181 (DCIST CRA).

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  1. Georgia Institute of Technology, Atlanta, GA, USA

    Harish Ravichandar, Kenneth Shaw & Sonia Chernova

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  1. Harish Ravichandar
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Correspondence to Harish Ravichandar.

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Ravichandar, H., Shaw, K. & Chernova, S. STRATA: unified framework for task assignments in large teams of heterogeneous agents. Auton Agent Multi-Agent Syst 34, 38 (2020). https://doi.org/10.1007/s10458-020-09461-y

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