Symbol Emergence in Robotics: A Survey

Humans can learn the use of language through physical interaction with their environment and semiotic communication with other people. It is very important to obtain a computational understanding of how humans can form a symbol system and obtain semiotic skills through their autonomous mental development. Recently, many studies have been conducted on the construction of robotic systems and machine-learning methods that can learn the use of language through embodied multimodal interaction with their environment and other systems. Understanding human social interactions and developing a robot that can smoothly communicate with human users in the long term, requires an understanding of the dynamics of symbol systems and is crucially important. The embodied cognition and social interaction of participants gradually change a symbol system in a constructive manner. In this paper, we introduce a field of research called symbol emergence in robotics (SER). SER is a constructive approach towards an emergent symbol system. The emergent symbol system is socially self-organized through both semiotic communications and physical interactions with autonomous cognitive developmental agents, i.e., humans and developmental robots. Specifically, we describe some state-of-art research topics concerning SER, e.g., multimodal categorization, word discovery, and a double articulation analysis, that enable a robot to obtain words and their embodied meanings from raw sensory--motor information, including visual information, haptic information, auditory information, and acoustic speech signals, in a totally unsupervised manner. Finally, we suggest future directions of research in SER.Comment: submitted to Advanced Robotic

Modelling the Developing Mind: From Structure to Change

This paper presents a theory of cognitive change. The theory assumes that the fundamental causes of cognitive change reside in the architecture of mind. Thus, the architecture of mind as specified by the theory is described first. It is assumed that the mind is a three-level universe involving (1) a processing system that constrains processing potentials, (2) a set of specialized capacity systems that guide understanding of different reality and knowledge domains, and (3) a hypecognitive system that monitors and controls the functioning of all other systems. The paper then specifies the types of change that may occur in cognitive development (changes within the levels of mind, changes in the relations between structures across levels, changes in the efficiency of a structure) and a series of general (e.g., metarepresentation) and more specific mechanisms (e.g., bridging, interweaving, and fusion) that bring the changes about. It is argued that different types of change require different mechanisms. Finally, a general model of the nature of cognitive development is offered. The relations between the theory proposed in the paper and other theories and research in cognitive development and cognitive neuroscience is discussed throughout the paper

Concept mapping, mind mapping argument mapping: What are the differences and do they matter?

In recent years, academics and educators have begun to use software mapping tools for a number of education-related purposes. Typically, the tools are used to help impart critical and analytical skills to students, to enable students to see relationships between concepts, and also as a method of assessment. The common feature of all these tools is the use of diagrammatic relationships of various kinds in preference to written or verbal descriptions. Pictures and structured diagrams are thought to be more comprehensible than just words, and a clearer way to illustrate understanding of complex topics. Variants of these tools are available under different names: “concept mapping”, “mind mapping” and “argument mapping”. Sometimes these terms are used synonymously. However, as this paper will demonstrate, there are clear differences in each of these mapping tools. This paper offers an outline of the various types of tool available and their advantages and disadvantages. It argues that the choice of mapping tool largely depends on the purpose or aim for which the tool is used and that the tools may well be converging to offer educators as yet unrealised and potentially complementary functions

Backwards is the way forward: feedback in the cortical hierarchy predicts the expected future

Clark offers a powerful description of the brain as a prediction machine, which offers progress on two distinct levels. First, on an abstract conceptual level, it provides a unifying framework for perception, action, and cognition (including subdivisions such as attention, expectation, and imagination). Second, hierarchical prediction offers progress on a concrete descriptive level for testing and constraining conceptual elements and mechanisms of predictive coding models (estimation of predictions, prediction errors, and internal models)