Gazing at Social Interactions Between Foraging and Decision Theory

• Published in: Frontiers in neurorobotics Vol. 15; p. 639999
• Main Authors: D'Amelio, Alessandro, Boccignone, Giuseppe
• Format: Journal Article
• Language: English
• Published: Switzerland Frontiers Research Foundation 30.03.2021; Frontiers Media S.A
• Subjects: Animal cognition; audio-visual attention; Computer applications; Decision making; Decision theory; drift-diffusion model; Food; Foraging behavior; gaze models; multimodal perception; Neuroscience; Robotics; social interaction; Social interactions; decision theory; perceptual decisions; drift-diffusion model; multimodal perception; social interaction; gaze models; audio-visual attention
• ISSN: 1662-5218; 1662-5218
• DOI: 10.3389/fnbot.2021.639999

Finding the underlying principles of social attention in humans seems to be essential for the design of the interaction between natural and artificial agents. Here, we focus on the computational modeling of gaze dynamics as exhibited by humans when perceiving socially relevant multimodal information. The audio-visual landscape of social interactions is distilled into a number of multimodal patches that convey different social value, and we work under the general frame of foraging as a tradeoff between local patch exploitation and landscape exploration. We show that the spatio-temporal dynamics of gaze shifts can be parsimoniously described by Langevin-type stochastic differential equations triggering a decision equation over time. In particular, value-based patch choice and handling is reduced to a simple multi-alternative perceptual decision making that relies on a race-to-threshold between independent continuous-time perceptual evidence integrators, each integrator being associated with a patch.