Computational and Robotic Models of Early Language Development: A Review

We review computational and robotics models of early language learning and development. We first explain why and how these models are used to understand better how children learn language. We argue that they provide concrete theories of language learning as a complex dynamic system, complementing traditional methods in psychology and linguistics. We review different modeling formalisms, grounded in techniques from machine learning and artificial intelligence such as Bayesian and neural network approaches. We then discuss their role in understanding several key mechanisms of language development: cross-situational statistical learning, embodiment, situated social interaction, intrinsically motivated learning, and cultural evolution. We conclude by discussing future challenges for research, including modeling of large-scale empirical data about language acquisition in real-world environments. Keywords: Early language learning, Computational and robotic models, machine learning, development, embodiment, social interaction, intrinsic motivation, self-organization, dynamical systems, complexity.Comment: to appear in International Handbook on Language Development, ed. J. Horst and J. von Koss Torkildsen, Routledg

A novel plasticity rule can explain the development of sensorimotor intelligence

Grounding autonomous behavior in the nervous system is a fundamental challenge for neuroscience. In particular, the self-organized behavioral development provides more questions than answers. Are there special functional units for curiosity, motivation, and creativity? This paper argues that these features can be grounded in synaptic plasticity itself, without requiring any higher level constructs. We propose differential extrinsic plasticity (DEP) as a new synaptic rule for self-learning systems and apply it to a number of complex robotic systems as a test case. Without specifying any purpose or goal, seemingly purposeful and adaptive behavior is developed, displaying a certain level of sensorimotor intelligence. These surprising results require no system specific modifications of the DEP rule but arise rather from the underlying mechanism of spontaneous symmetry breaking due to the tight brain-body-environment coupling. The new synaptic rule is biologically plausible and it would be an interesting target for a neurobiolocal investigation. We also argue that this neuronal mechanism may have been a catalyst in natural evolution.Comment: 18 pages, 5 figures, 7 video

Conceptual Model for Developing Creativity in Batik Industry

The purpose of this research is to develop a conceptual model of creativity in batik industry. This model was developed by conducting a study from previous research that discuss important factors for the development of creativity. This conceptual model was built based on four variable, namely creative person, intrinsic motivation, job skills training, and creative organizational climate. Creative person will stimulate the creativity development in batik industry. A creative person are more able to improve their creativity if they have intrinsic motivation, given some training that related with the job skills they needed, and supported by organization that have positive climate (climate in organization that respects creativity, provide opportunities, time, facilities, infrastructure and incentives to employees to think about, designing, researching and developing new products that better and more innovative). For the further research, this study can be continued by testing the model empirically through distributing the questionnaire to some participant of SMEs and processing data from the results of questionnaire distribution using the data processing software like SPSS, LISRELL, etc

Information driven self-organization of complex robotic behaviors

Information theory is a powerful tool to express principles to drive autonomous systems because it is domain invariant and allows for an intuitive interpretation. This paper studies the use of the predictive information (PI), also called excess entropy or effective measure complexity, of the sensorimotor process as a driving force to generate behavior. We study nonlinear and nonstationary systems and introduce the time-local predicting information (TiPI) which allows us to derive exact results together with explicit update rules for the parameters of the controller in the dynamical systems framework. In this way the information principle, formulated at the level of behavior, is translated to the dynamics of the synapses. We underpin our results with a number of case studies with high-dimensional robotic systems. We show the spontaneous cooperativity in a complex physical system with decentralized control. Moreover, a jointly controlled humanoid robot develops a high behavioral variety depending on its physics and the environment it is dynamically embedded into. The behavior can be decomposed into a succession of low-dimensional modes that increasingly explore the behavior space. This is a promising way to avoid the curse of dimensionality which hinders learning systems to scale well.Comment: 29 pages, 12 figure

Autonomy and autonomy disturbances in self-development and psychopathology: research on motivation, attachment, and clinical process

Self-determination theory (SDT) maintains that the adequate support and satisfaction of individuals' psychological needs for autonomy, competence, and relatedness promotes the gradual unfolding of individuals' integrative tendencies, as manifested through intrinsic motivation, internalization, identity development, and integrative emotion regulation. At the same time, the thwarting of these same psychological needs and the resultant need frustration is presumed to evoke or amplify a variety of psychopathologies, many of which involve autonomy disturbances. We begin by defining what autonomy involves and how socializing agents, particularly parents, can provide a nurturing (i.e., need-supportive) environment, and we review research within the SDT literature that has shed light on various integrative tendencies and how caregivers facilitate them. In the second part of this chapter, we detail how many forms of psychopathology involve autonomy disturbances and are associated with a history of psychological need thwarting. We especially focus on internally controlling regulation in internalizing disorders; impairments of internalization in conduct disorders and antisocial behavior; and fragmented self-functioning in borderline and dissociative disorders. The role of autonomy support as an ameliorative factor in treatment settings is then discussed among other translational issues. Finally we highlight some implications of recognizing the important role of basic psychological needs for both growth-related and pathology-related processes

What do faculties specializing in brain and neural sciences think about, and how do they approach, brain-friendly teaching-learning in Iran?

Objective: to investigate the perspectives and experiences of the faculties specializing in brain and neural sciences regarding brain-friendly teaching-learning in Iran. Methods: 17 faculties from 5 universities were selected by purposive sampling (2018). In-depth semi-structured interviews with directed content analysis were used. Results: 31 sub-subcategories, 10 subcategories, and 4 categories were formed according to the “General teaching model”. “Mentorship” was a newly added category. Conclusions: A neuro-educational approach that consider the roles of the learner’s brain uniqueness, executive function facilitation, and the valence system are important to learning. Such learning can be facilitated through cognitive load considerations, repetition, deep questioning, visualization, feedback, and reflection. The contextualized, problem-oriented, social, multi-sensory, experiential, spaced learning, and brain-friendly evaluation must be considered. Mentorship is important for coaching and emotional facilitation