About

Arvin Agah is a prominent robotics and artificial intelligence researcher whose work spans human-robot interaction, neural network-based robot learning, and multi-robot systems. His research has significantly advanced our understanding of how humans psychologically and socially engage with intelligent machines, most notably demonstrated in his highly cited 2001 study on the psychological effects of mobile personal robot behavior, which has garnered 159 citations and remains a foundational reference in social robotics. Agah has made substantial technical contributions to robotic learning, particularly in solving the complex problem of inverse kinematics using modular neural network architectures — work that addresses the inherent discontinuities and multi-valued nature of robotic arm motion, accumulated across multiple influential publications. His 2000 taxonomy of human-intelligent systems interactions helped establish a theoretical framework that continues to guide researchers in the field. Beyond individual robots, Agah explored collective intelligence through evolutionary and phylogenetic learning in robot colonies, autonomous soccer-playing strategies, and distributed search teams. His 2016 work on social robotics reflects a career-long commitment to bridging machine capability with human experience. With contributions spanning nearly three decades, Agah's research has shaped both the technical foundations and human-centered dimensions of modern robotics.

Research Focus

Key Achievements

17
H-Index
60
Papers
924
Total Citations
15
Avg Citations/Paper
🏆 Most Cited Paper
Psychological Effects of Behavior Patterns of a Mobile Personal Robot
159 citations · 2001
📈 Most Prolific Year: 2002 (12 Papers)
🤝 Key Collaborators: 76
🏛 Institutions: University of Kansas, National Institute of Advanced Industrial Science and Technology, University of Tennessee at Knoxville, University of Southern California

Top Papers

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    Social Robotics
    34 citations · 2016
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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 33 days ago