Yoshihiro Maruyama

Australian National University

Papers

3

Total Citations

27

H-Index

3

About

Yoshihiro Maruyama is a pioneering researcher at the intersection of artificial intelligence, cognitive science, and human-computer interaction. His work fundamentally challenges traditional boundaries between symbolic and statistical approaches to cognition, advocating for an integrated AI framework that synthesizes logical reasoning with data-driven learning. In his most cited work, "Symbolic and Statistical Theories of Cognition: Towards Integrated Artificial Intelligence" (2021, 20 citations), Maruyama proposes novel architectures that bridge these paradigms, offering a path toward more robust and human-like AI systems. He further explores the structural underpinnings of rationality and cognitive bias through the lens of quantum cognitive science, as detailed in his 2020 paper (4 citations), where he applies quantum probability frameworks to model human decision-making anomalies. Maruyama also investigates the coevolutionary dynamics between humans and AI in scientific discovery and robotics (2022, 3 citations), emphasizing bidirectional adaptation. His interdisciplinary contributions have garnered attention for their theoretical depth and practical implications, positioning him as a leading voice in the quest for truly integrated artificial intelligence.

Research Focus

Key Achievements

3
H-Index
3
Papers
27
Total Citations
9
Avg Citations/Paper
🏆 Most Cited Paper
Symbolic and Statistical Theories of Cognition: Towards Integrated Artificial Intelligence
20 citations · 2021
📈 Most Prolific Year: 2021 (1 Papers)
🤝 Key Collaborators: 0
🏛 Institutions: Australian National University

Top Papers

  1. 1
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  3. 3

Contact & Links

Available for collaboration
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