Using robots to understand social behaviour

Abstract

A major challenge in studying social behavior stems from the need to disentangle the behavior of each individual from the resulting collective. One way to overcome this problem is to constructa model of the behavior of an individual, and observe whether combining many such individuals leads to the predicted outcome.Thiscanbeachievedbyusingrobots.Inthisreviewwediscussthestrengthsandweaknessesof such an approach for studies of social behavior. We find that robots -whether studied in groups of researchers from a range of fields, as it poses interesting questions from mechanistic and evolutionary viewpoints. Many approaches have been used to study social behavior. These approaches can be classified over a scale of "situatedness", which we define as the extent to which individuals are embedded in an environment that can be sensed and modified by those individuals (Varela et al., 1991;Clark, 1996). The situatedness spectrum ranges from abstract mathematicalmodelsononeendtofieldworkinnaturalhabitatsattheotherend (Fig.1).

Information Flow in Animal-Robot Interactions

“…In social organisms that move in groups, it has been shown that the actions of a few nearest neighbors contribute largely to such cues [2]. In this respect, determining the flow of information between interacting individuals can reveal how they prioritize sensory modalities [3], infer the directionality of information flow [4][5][6], quantify leadership roles in animal groups [7], and determine the effectiveness of engineered stimuli in the laboratory studies [8][9][10]. These motivations to measure information flow are similar to those encountered in the study of networks of dynamical systems, where tools from information theory have been used to detect causal relationships [11][12][13], locate driving nodes [14], and quantify the strength of network connections [15].…”

Evolutionary Robotics: Model or Design?

“…However, this potential can be easily dissipated without a clear commitment to produce high-quality studies that focus on the relevant aspects of either modeling or design. To maximize the potential of ER, it is useful to recall a distinction proposed by Mitri et al (2012) about the usage of (evolutionary) robotics to model biological systems, which may be either exploratory or hypothesis-driven. In the former, experiments are conducted to understand the possibilities offered by robotics and ER as a modeling tool, with the goal of providing existence proofs and producing novel testable hypotheses (Harvey et al, 2005).…”

“…In this respect, it is not always necessary to refer to a real robotic system, but simulated agents can be sufficient as long as situatedness and embodiment are properly accounted for [e.g., the predator-prey interaction studied by Olson et al (2013)]. Real robotic systems instead are mostly useful when the physical body and the way in which the world is perceived through physical sensors may have a bearing on the phenomena under study [see a similar discussion by Mitri et al (2012)]. …”

Towards a Universal Test of Social Intelligence

“…The understanding of social behaviours has also been studied from the perspective of robotics, where robots (physical or simulated) are used in order to better understand the interaction between the agents [74]. These studies are performed by avoiding some convenient assumptions on their designs or models and adjusting their robots to a more realistic vision of the environment.…”