Modelling Human Understanding of Thematic Roles with Motion Heuristics

Humans can understand event roles like agent and patient within videos of simple shapes moving around just using simple motion heuristics. As existing computational systems do not directly address human understanding of these events, we develop the first computational model that can simulate human performance in these tasks. We develop an approach heuristic that can simulate how human recognition of chasing is influenced by the angle that the chaser uses to approach the chasee. We also created a causality heuristic that captures human sensitivity to contact between the pusher and the pushee, as well as a delay in launching. Careful modelling of psychological studies of infants and adults behaviour can yield insights that may enhance computational systems for action understanding.