Diego Cajal
Papers
1
Total Citations
2
H-Index
1
About
Diego Cajal is a researcher in evolutionary robotics and computational modelling of social behaviour, whose work bridges the gap between biological inspiration and artificial intelligence. His primary research areas include social habit formation, organismically inspired robotics, and the evolution of collective behaviours in artificial agents. Cajal's most notable contribution is his 2019 paper "Towards modelling social habits: an organismically inspired evolutionary robotics approach," which proposes a novel framework for simulating how social habits emerge and stabilise in robotic systems through evolutionary processes. This work draws on principles from developmental biology and ethology to create more adaptive, socially intelligent robots. While his citation count is still growing—with the 2019 paper currently at 2 citations—Cajal's research represents an important step toward understanding the mechanistic underpinnings of social behaviour in both natural and artificial systems. His approach offers a fresh perspective on how robots can learn and internalise social norms, with potential applications in human-robot interaction and collective robotics. Cajal's work is particularly relevant for researchers interested in the intersection of evolutionary computation, social cognition, and embodied intelligence.
Research Focus
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Top Papers
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