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Adaptive Collaboration Based on the E-CARGO Model

Haibin Zhu, Ming Hou, Mengchu Zhou

Source Title: International Journal of Agent Technologies and Systems (IJATS)4(1)

ISSN: 1943-0744|EISSN: 1943-0752|EISBN13: 9781466610613|DOI: 10.4018/jats.2012010104

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MLA

Zhu, Haibin, et al. "Adaptive Collaboration Based on the E-CARGO Model." IJATS vol.4, no.1 2012: pp.59-76. http://doi.org/10.4018/jats.2012010104

APA

Zhu, H., Hou, M., & Zhou, M. (2012). Adaptive Collaboration Based on the E-CARGO Model. International Journal of Agent Technologies and Systems (IJATS), 4(1), 59-76. http://doi.org/10.4018/jats.2012010104

Chicago

Zhu, Haibin, Ming Hou, and Mengchu Zhou. "Adaptive Collaboration Based on the E-CARGO Model," International Journal of Agent Technologies and Systems (IJATS) 4, no.1: 59-76. http://doi.org/10.4018/jats.2012010104

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Abstract

Adaptive Collaboration (AC) is essential for maintaining optimal team performance on collaborative tasks. However, little research has discussed AC in multi-agent systems. This paper introduces AC within the context of solving real-world team performance problems using computer-based algorithms. Based on the authors’ previous work on the Environment-Class, Agent, Role, Group, and Object (E-CARGO) model, a theoretical foundation for AC using a simplified model of role-based collaboration (RBC) is proposed. Several parameters that affect team performance are defined and integrated into a theorem, which showed that dynamic role assignment yields better performance than static role assignment. The benefits of implementing AC are further proven by simulating a “future battlefield” of remotely-controlled robotic vehicles; in this scenario, team performance clearly benefits from shifting vehicles (or roles) using a single controller. Related research is also discussed for future studies.

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Adaptive Collaboration Based on the E-CARGO Model

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