The detection of a human’s intended behavior is one of the most important skills that a social robot should have in order to become acceptable as a part of human society, because humans are used to understand the actions of other humans in a goal-directed manner and they will expect the social robot to behave similarly. A breakthrough in this area can advance several research branches related to social intelligence such as learning by imitation and mutual adaptation. To achieve this (...) goal the robot needs to integrate all possible evidence of intention and neglect the unintended behavior, and a complete solution should use low-level signal processing and high-level reasoning. This work explores the low-level signal processing part of the solution by proposing an interactive adaptive perception scheme that uses four important features of human behavior to amplify the signals originating from intended behavior with respect to signals originating from unintended behavior and other noise sources such as instrumental noise. This work follows the vision that intelligence is not only a function of a centralized sophisticated artificial brain, but can be presented in different forms in the entire robot including its perception and motion systems (the mind is not contained in the brain, but distributed in every cell in the body). A simple example of using the proposed scheme was implemented and the results of two experiments with it are also presented. (shrink)

boundaries. It is impossible to do good science without having an appreciation for the problems and concepts in the other levels of abstraction (at least in the direction from biology towards physics), but there are whole sets of tools, methods of analysis, theories and explanations within each discipline which do not cross those boundaries.

This paper presents an approach to solve the symbol grounding problem within the framework of embodied cognitive science. It will be argued that symbolic structures can be used within the paradigm of embodied cognitive science by adopting an alternative definition of a symbol. In this alternative definition, the symbol may be viewed as a structural coupling between an agent's sensorimotor activations and its environment. A robotic experiment is presented in which mobile robots develop a symbolic structure from scratch by engaging (...) in a series of language games. In this experiment it is shown that robots can develop a symbolic structure with which they can communicate the names of a few objects with a remarkable degree of success. It is further shown that, although the referents may be interpreted differently on different occasions, the objects are usually named with only one form. (shrink)