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Children are considered to develop various kinds of their social abilities in communication with their caregivers. Developmental researchers have revealed the quality of the caregiver-child attachment heavily affects the children's developmental passway and sometimes threatens their healthy development. For understanding developmental mechanism under the caregiver-child attachment, a number of theoretical...
We study the computational complexity of adapting a reactive architecture to meet task constraints. This computational problem has application in a wide variety of fields, including cognitive and evolutionary robotics and cognitive neuroscience. We show that—even for a rather simple world and a simple task—adapting a reactive architecture to perform a given task in the given world is NP-hard. This...
Children rapidly learn the inventory of phonemes used in their native tongues. Computational approaches to learning phoneme boundaries from speech data do not yet reach the level of human performance. We present an algorithm that operates on, qualitatively, similar data to those children receive: natural language utterances from multiple speakers. Our algorithm is unsupervised and discovers phoneme...
The question of how the mirror neuron system (MNS) develops has attracted increased attention of researchers. Among various hypotheses, a widely accepted model is associative sequence learning, which acquires the MNS as a by-product of sensorimotor learning. The model, however, cannot discriminate self from others since it adopts too much simplified sensory representations. We propose a computational...
In this paper we propose a sequential pattern mining method to analyze multimodal data streams using a quantitative temporal approach. While the existing algorithms can only find sequential orders of temporal events, this paper presents a new temporal data mining method focusing on extracting exact timings and durations of sequential patterns extracted from multiple temporal event streams. We present...
A developing agent learns a model of the world by observing regularities occurring in its sensory inputs. In a continuous domain where the model is represented by a set of rules, a significant part of the task of learning such a model is to find appropriate intervals within the continuous state variables, such that these intervals can be used to define rules whose predictions are reliable. We propose...
Traditional view stresses the role of errors in the learning process. The result obtained from our experiment with older infants suggested that omitting the errors during learning can also be beneficial. We propose that a temporal decrease in learning from negative feedback could be an efficient mechanism behind infant learning new skills. Herein, we claim that disregarding the errors is tightly connected...
Recently, a novel framework has been proposed for intrinsically motivated reinforcement learning (IMRL) in which a learning agent is driven by rewards that include not only information about what the agent must accomplish in order to “survive”, but also additional reward signals that drive the agent to engage in other activities, such as playing or exploring, because they are “inherently enjoyable”...
This study investigates the effect of local task difficulty on children's tendency to combine pieces of information into larger wholes. The particular hypothesis is that the emergence of higher-order Gestalts is guided neither by innate capabilities nor by laborious thought processes. Instead, it is - at least partly - tied to the difficult of the local task, adaptively allowing the mind to reduce...
How to teach science to young children? Despite extensive research on the importance of direct instruction, the general recommendation is to provide children with an opportunity to explore a domain on their own. However, it is not clear how self-guided explorations could help children overcome misconceptions. The current paper pursues this question within the domain of sinking objects - a domain in...
This paper proposes a method for acquiring categories in one modality and mappings between these categories and those in other modalities. Subjective consistency through multimodal mappings is introduced to judge to what extent a perceived signal and inferred ones from other modalities are reliable for categorization and mapping. Based on the proposed method, a simulated infant robot learns categories...
This paper presents the hypothesis that intrinsic, apparently goal-free, motor-centric activity is a fundamental and necessary component of cognitive development in truly autonomous intelligent agents, both human and artificial.
The morphology of an embodied agent heavily influences the characteristics of sensory signals induced during sensorimotor activity. In order to facilitate later information processing, it is desirable to couple sensors and actuators in a way such that the agent's actions induce well structured sensory feedback. In this work, we empirically investigate the meaning of “well structured” with respect...
An overview of the NMF (non-negative matrix factorization) approach for word acquisition from auditory inputs is given. The method can link acoustic realizations of spoken words with information observed in other modalities. The method is applied to the acquisition of a small set of keywords embedded in carrier sentences. A phonetic description is linked to the learned representations which are otherwise...
This paper discusses the effect of different embodiments on the development of shared meanings between agents, and how language can help to overcome this difference. Using color as an exemplary case, we discuss how despite perceptual differences agents can develop a common understanding of color categories. This phenomenon is investigated through computational modeling of agents with different perceptual...
A series of neural network simulations investigated whether the original Ebbinghaus' German non-sense syllables would be activated and processed in their raw format, or needed association with a preceding neighboring item to be best remembered. The ‘predictive’ autoassociative network was unable to reduce the error rate below .50, and node activation in the Hinton diagram appeared to be random. Adding...
We introduce a novel dynamical model for visual attention based on stimulus induced population dynamics in an oscillatory medium, and apply this model to active perception of social content in still images. Making use of images from the newly emerging face-to-face paradigm in social developmental psychology, we show that this model generates patterns of eye movements that exhibit increased frequency...
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