Deep Learning and Game Theory for AI-Enabled Human-Robot Collaboration System Design in Industry 4.0

Xing, Yuan; Hou, Dongfang; Liu, Jason; Yuan, Holly; Verma, Abhishek; Shi, Wei

doi:10.1109/ccwc60891.2024.10427753

Cited by 2 publications

(1 citation statement)

References 17 publications

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“…Xing et al [53] present an innovative approach to optimising path planning for robots in a human-robot collaboration environment typical of Industry 4.0. The study addresses the challenges faced by robots in navigating complex, dynamic environments shared with human Workers.…”

Section: Game Theory and Aimentioning

confidence: 99%

Strategic Management of Workforce Diversity: An Evolutionary Game Theory Approach as a Foundation for AI-Driven Systems

Talajić,

Vrankić,

Pejić Bach

2024

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In the complex organisational landscape, managing workforce diversity effectively has become crucial due to rapid technological advancements and shifting societal values. This study explores strategic workforce management through the novel methodological framework consisting of the evolutionary game theory concept integrated with replicator dynamics and traditional game theory, addressing a notable gap in the literature and suggesting an evolutionarily stable workforce structure. Key findings indicate that targeted rewards for the most Enthusiastic employee type can reduce overall costs and enhance workforce efficiency, although managing a diverse team remains complex. The study reveals that while short-term incentives boost immediate productivity, long-term rewards facilitate favourable behavioural changes, which are crucial for sustaining organisational performance. Additionally, the role of artificial intelligence (AI) is highlighted, emphasising its potential to integrate with these theoretical models, thereby enhancing decision-making processes. The study underscores the importance of strategic leadership in navigating these dynamics, suggesting that leaders must tailor their approaches to balance short-term incentives and long-term rewards to maintain an optimal workforce structure.

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Section: Game Theory and Aimentioning

confidence: 99%

Strategic Management of Workforce Diversity: An Evolutionary Game Theory Approach as a Foundation for AI-Driven Systems

Talajić,

Vrankić,

Pejić Bach

2024

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Challenges and Opportunities in the Implementation of AI in Manufacturing: A Bibliometric Analysis

Espina-Romero,

Gutiérrez Hurtado,

Ríos Parra

et al. 2024

Sci

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This study explores the evolution and impact of research on the challenges and opportunities in the implementation of artificial intelligence (AI) in manufacturing between 2019 and August 2024. By addressing the growing integration of AI technologies in the manufacturing sector, the research seeks to provide a comprehensive view of how AI applications are transforming production processes, improving efficiency, and opening new business opportunities. A bibliometric analysis was conducted, examining global scientific production, influential authors, key sources, and thematic trends. Data were collected from Scopus, and a detailed review of key publications was carried out to identify knowledge gaps and unresolved research questions. The results reveal a steady increase in research related to AI in manufacturing, with a strong focus on automation, predictive maintenance, and supply chain optimization. The study also highlights the dominance of certain institutions and key authors driving this field of research. Despite the progress, significant challenges remain, particularly regarding the scalability of AI solutions and ethical considerations. The findings suggest that while AI holds considerable potential for the manufacturing industry, more interdisciplinary research is needed to address existing gaps and maximize its benefits.

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Deep Learning and Game Theory for AI-Enabled Human-Robot Collaboration System Design in Industry 4.0

Cited by 2 publications

References 17 publications

Strategic Management of Workforce Diversity: An Evolutionary Game Theory Approach as a Foundation for AI-Driven Systems

Strategic Management of Workforce Diversity: An Evolutionary Game Theory Approach as a Foundation for AI-Driven Systems

Challenges and Opportunities in the Implementation of AI in Manufacturing: A Bibliometric Analysis

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