
doi: 10.1075/is.7.2.04kap
This article discusses the concept of joint attention and the different skills underlying its development. Research in developmental psychology clearly states that the development of skills to understand, manipulate and coordinate attentional behavior plays a pivotal role for imitation, social cognition and the development of language. However, beside the fact that joint attention has recently received an increasing interest in the robotics community, existing models concentrate only on partial and isolated elements of these phenomena. In the line of Tomasello’s research, we argue that joint attention is much more than simultaneous looking because it implies a shared intentional relation to the world. This requires skills for attention detection, attention manipulation, social coordination and, most importantly, intentional understanding. After defining joint attention and its challenges, the current state-of-the-art of robotic and computational models relevant for this issue is discussed in relation to a developmental timeline drawn from results in child studies. From this survey, we identify open issues and challenges that still need to be addressed to understand the development of the various aspects of joint attention and conclude with the potential contribution of robotic models.
Behavioral Analysis, Developmental Psychology, Robotics
Behavioral Analysis, Developmental Psychology, Robotics
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 112 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 1% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
