Three decision-making rules allowed the DPMP model to predict nearly 80% of players’ cow herding choices and their responses.
A cattle herding game boosts our understanding of human navigation, enhancing AI and robot interactions.
A game involving virtual cattle herding has provided new insights into human decision-making around movement and navigation.
The video game exercise was part of a study aimed at exploring how dynamical perceptual-motor primitives (DPMPs) can be applied to replicate human decision-making.
The results showed that a basic DPMP navigation model could closely match participants’ movement paths, accurately predicting nearly 80 percent of their target choices using a straightforward rule.
The findings could enhance interactions with AI and improve robotic movement in future applications.
Researchers from Macquarie University in Australia, Scuola Superiore Meridionale, the University of Naples Federico II, the University of Bologna in Italy, and University College London in the UK conducted the experiment.