Alfredo Cuesta‐Infante
Papers
2
Total Citations
403
H-Index
2
About
Alfredo Cuesta‐Infante is a leading voice at the intersection of artificial intelligence, data science, and robotics. His research primarily focuses on harnessing machine and deep learning to solve complex, real-world problems, from advancing computational intelligence systems to enabling autonomous navigation. His highly influential work, "Artificial intelligence within the interplay between natural and artificial computation" (312 citations), provides a seminal overview of how AI is reshaping society, economy, and education, marking a key contribution to the field. Demonstrating the practical power of reinforcement learning, his paper on "Mobile Robot Path Planning Using a QAPF Learning Algorithm" (91 citations) introduces a novel Q-learning approach for navigating both known and unknown environments. This work has become a cornerstone for researchers developing self-learning robotic systems. Through these contributions, Cuesta‐Infante has established himself as a pivotal figure bridging theoretical advances in AI with tangible applications in autonomous systems and data-driven innovation.
Research Focus
Key Achievements
Top Papers
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