John Murray
Papers
8
Total Citations
59
H-Index
5
About
John Murray is a researcher specializing in human-robot interaction, affective computing, and the application of cognitive biases in robotic systems. His most significant contributions explore a novel and counterintuitive approach: rather than striving for perfect, rational robotic behavior, Murray investigates how deliberately introducing human-like cognitive imperfections into robots can foster more natural and enduring social relationships between humans and machines. His most cited work, "The Effects of Cognitive Biases and Imperfectness in Long-Term Robot-Human Interactions" (2016, 16 citations), alongside related studies on misattribution and self-serving bias, demonstrates that robots exhibiting recognizably human flaws — such as forgetfulness or denial of defeat — can become more relatable and likeable companions. His 2014 case study on misattribution (11 citations) offered an influential model for building long-term robotic social relationships grounded in these principles. Murray has also contributed meaningfully to the broader fields of emotion modeling and affective virtual agents, co-organizing the International Workshop on Affective-Aware Virtual Agents and Social Robots (2009, 11 citations). His body of work, accumulating nearly 60 citations, provides a thought-provoking framework for designing companion robots that resonate more deeply with human psychology.
Research Focus
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