Interactivist approach to representation in epigenetic agents

Interactivism is a vast and rather ambitious philosophical and theoretical system originally developed by Mark Bickhard, which covers plethora of aspects related to mind and person. Within interactivism, an agent is regarded as an action system: an autonomous, self-organizing, self-maintaining entity, which can exercise actions and sense their effects in the environment it inhabits. In this paper, we will argue that it is especially suited for treatment of the problem of representation in epigenetic agents. More precisely, we will elaborate on process-based ontology for representations, and will sketch a way of discussing about architectures for epigenetic agents in a general manner

Interaction and Experience in Enactive Intelligence and Humanoid Robotics

We overview how sensorimotor experience can be operationalized for interaction scenarios in which humanoid robots acquire skills and linguistic behaviours via enacting a “form-of-life”’ in interaction games (following Wittgenstein) with humans. The enactive paradigm is introduced which provides a powerful framework for the construction of complex adaptive systems, based on interaction, habit, and experience. Enactive cognitive architectures (following insights of Varela, Thompson and Rosch) that we have developed support social learning and robot ontogeny by harnessing information-theoretic methods and raw uninterpreted sensorimotor experience to scaffold the acquisition of behaviours. The success criterion here is validation by the robot engaging in ongoing human-robot interaction with naive participants who, over the course of iterated interactions, shape the robot’s behavioural and linguistic development. Engagement in such interaction exhibiting aspects of purposeful, habitual recurring structure evidences the developed capability of the humanoid to enact language and interaction games as a successful participant

Cultural robotics : The culture of robotics and robotics in culture

Copyright 2013 Samani et al.; licensee InTech. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly citedIn this paper, we have investigated the concept of "Cultural Robotics" with regard to the evolution o social into cultural robots in the 21st Century. By defining the concept of culture, the potential development of culture between humans and robots is explored. Based on the cultural values of the robotics developers, and the learning ability of current robots, cultural attributes in this regard are in the process of being formed, which would define the new concept of cultural robotics. According to the importance of the embodiment of robots in the sense of presence, the influence of robots in communication culture is anticipated. The sustainability of robotics culture based on diversity for cultural communities for various acceptance modalities is explored in order to anticipate the creation of different attributes of culture between robot and humans in the futurePeer reviewe

Generation of Evaluation Function for Lige-time Learning of An Intelligent Robot

This paper deals with a mobile robot with structured intelligence. The robot interacts with a dynamic environment. The evaluation criteria or functions are the strategy for the behavior acquisition. Generally, it is difficult for human operators to describe internal models of the robot because the organization of the robot is quite different from that of a human. In the optimization, the evaluation function is generally given by human operators beforehand. It is easy to give the evaluation functions if the environmental condition is easy and fixed. But the robot must interact with dynamic, uncertain and unknown environments or human operators. Therefore, the robot should generate the evaluation criteria by itself based on its embodiment. A human improves its behavior by using and changing its evaluation criteria as adaptive processes. The robot also has to acquire their evaluation criteria through life-time learning. Therefore, we apply genetic programming (GP) for generating evaluation functions. The result of computer simulation shows that GP can generate the evaluation function suitable to the facing environments, the given tasks, and the robot

Human-Machine Communication: Complete Volume. Volume 1

This is the complete volume of HMC Volume 1