In cognitive science, computation is largely accompanied with representational theory of mind. Yet, it remains unclear whether this companionship also appears in the realm of sensorimotor control. Grush’s (2004) and Pezzulo’s (2008, 2011) account of anticipatory representations provide a limited answer, as they are only suitable for forward models, but not the entire sensorimotor control. Rescorla’s (2016) representational explanation for sensorimotor psychology addresses several intentional states considered in Bayesian inference and optimal modeling. However, the above accounts does not explain how motor commands are produced and chosen in the course of sensorimotor control for maintaining accuracy of goal-achievement. The present paper aims to explain it with a representational account by considering instrumental representations of sensorimotor control, which appear at the intermediate level and are exemplified by motor commands and costs. Such representations do not presume decouplability, as they need to run on-line in the maintenance of accuracy.

Pezzulo (2008, 2011) and Grush (2004) contend for embodied cognitive science but interpret representations of motor behaviors as grounded on predictive internal models; those representations are referring-based. By contrast, the present paper contends that the motor control is ground on both referring-based representation (as manifest in forward models) and non-referring-based representation (as manifest in inverse models); the latter is pragmatic representation with the following six characteristics: perspective, changing perspectives, normativity of the goal, planning, coordination, and motor learning by refining inverse models. This is an internal version of the action-oriented representation.