Modelling Specialists and Generalists in the Task Allocation Problem – UROP Spring Symposium 2021

Modelling Specialists and Generalists in the Task Allocation Problem

Jojo Lee

Jojo Lee

Pronouns: she/her

Research Mentor(s): Peter Erdi, Visiting Professor /Henry Luce Professor of Complex Systems Studies
Research Mentor School/College/Department: Center for the Study of Complex Systems, College of Literature, Science, and the Arts
Presentation Date: Thursday, April 22, 2021
Session: Session 6 (4pm-4:50pm)
Breakout Room: Room 20
Presenter: 2

Event Link


Successful teams have a balanced range of skillsets. Agents – those autonomous entities responsible for completing tasks – are often functionally diverse, with different strengths and capabilities. Some will be generalists, completing a wide range of tasks. Others will be specialists with narrower capabilities, but higher performance at the tasks they’re capable of. We hypothesise that problem-solving teams attempting task-allocation problems can strike an optimal balance between specialists and generalists. Too many specialists may leave certain agents overloaded and tasks incomplete. Too many generalists may keep everyone busy, but slow the team down. We anticipate that peak performance will make use of individual strengths while ensuring no skill gaps exist. Our agent based-model allows us to selectively manipulate generalist-specialist ratios under different task allocation strategies. The computational approach looks at functional diversity from a theoretical perspective, making our findings generalizable over many fields. We hope our insights about team performance optimization can guide processes in science and management in an increasingly intricate world.

Authors: Caroline Skalla, Jojo Lee
Research Method: Library/Archival/Internet Research

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