Aligning Teams to the Future: Adapting Human-Machine Teams via Free Energy
| Autor: | Daniel Serfaty, Krishna R. Pattipati, Georgiy Levchuk, Adam Fouse, Robert McCormack, Nathan Schurr |
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| Rok vydání: | 2019 |
| Předmět: | |
| Zdroj: | Advances in Intelligent Systems and Computing ISBN: 9783030110505 IHSI |
| DOI: | 10.1007/978-3-030-11051-2_71 |
| Popis: | Future hybrid human-machine teams will need to optimize their performance in uncertain environments by adapting their team structure. To address this need, we have developed a framework based on minimization of variational free energy, an information theoretic measure that has been shown to account for a variety of biological self-organizing phenomena. This paper proposes a novel approach to balance team structure by adapting roles and relationships based upon this framework. We apply this approach to evaluate possible structures for an infantry squad of human soldiers and autonomous systems. Using our STATES team simulation environment, we simulate mission performance for these teams and demonstrate that this approach enables a 12-person team to achieve performance results on par with a 15-person traditional team in terms of mission execution time. We argue that these results indicate that the free energy approach will lead to better hybrid team adaptations and improved performance. |
| Databáze: | OpenAIRE |
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