Learning where to look with movement-based intrinsic motivations: a bio-inspired model

Most sophisticated mammals, in particular primates, interact with the world to acquire knowledge and skills later exploitable to obtain biologically relevant resources. These interactions are driven by intrinsic motivations. Recent research on brain is revealing the system of neural structures, pivoting on superior colliculus, underlying trial-and-error learning processes guided by movement-detection, one important element of one speci?c type of intrinsic motivation mechanism. Here we present a preliminary computational model of such system guiding the acquisition of overt attentional skills. The model is formed by bottom-up attentional components, exploiting the intrinsic properties of the scene, and top-down attentional components, learning under the guidance of movement-based intrinsic motivation. The model is tested with a simple task, inspired by the \u27gaze- contingency paradigm\u27 proposed in cognitive psychology, where looking some portions of the environment can directly change it. The tests of the model show how its integrated components can learn skills causing relevant changes in the environment while ignoring changes non-contingent to own action. The model also allows the presentation of a wider research agenda directed to build biologically plausible models of the interaction between overt attention control and intrinsic motivations

Robotics Attack!

No abstract availabl

A McKibben muscle arm learning equilibrium postures

In designing artificial systems for studying motor control in humans and other organisms a key point to consider is the complexity reached by brain and body in their developmental stages. An artificial system whose brain and body complexity is shaped according to developmental stages might allow understanding weather, for example, newborn infants, infants, and adults use different neural mechanisms to cope with the same motor control problems. This article proposes an artificial system which aims at becoming a tool to study this type of problems. The system has a brain and body endowed with a set of minimal bio-mimetic features: (a) neural maps activated by receptive fields; (b) connections plasticity changed by Hebbian rule; (c) robotic arm actuated by a McKibben muscle. The arm autonomously learns to reach specific positions in space under the effect of gravity and for different load conditions. The results suggest that a fast and incremental goalaction mapping formation could constitute the computational mechanism underlying the neural growth and plasticity of an early developed brain at the onset of reaching. The same mechanism also allows a first approximate solution for load compensation avoiding the use of more sophisticated internal models (developed in further brain and body developmental stages). This paper aims to be a preliminary study on the feasibility of this approach

Modular and hierarchical brain organization to understand assimilation, accommodation and their relation to autism in reaching tasks: a developmental robotics hypothesis

By "assimilation" the child embodies the sensorimotor experience into already built mental structures. Conversely, by "accommodation" these structures are changed according to the child\u27s new experiences. Despite the intuitive power of these concepts to trace the course of sensorimotor development, they have gradually lost ground in psychology. This likely for a lack of brain related views capturing the dynamic mechanisms underlying them. Here we propose that brain modular and hierarchical organization is crucial to understanding assimilation/accommodation. We devised an experiment where a bio-inspired modular and hierarchical mixture-of-experts model guides a simulated robot to learn by trial-and-error different reaching tasks. The model gives a novel interpretation of assimilation/accommodation based on the functional organization of the experts allocated through learning. Assimilation occurs when the model adapts a copy of the expert trained for solving a task to face another task requiring similar sensorimotor mappings. Experts storing similar sensorimotor mappings belong to the same functional module. Accommodation occurs when the model uses non-trained experts to face tasks requiring different sensorimotor mappings (generating a new functional group of experts). The model provides a new theoretical framework to investigate impairments in assimilation/accommodation the autistic syndrome

Motivating Children with Autism to Communicate and Interact Socially Through the "+me" Wearable Device

No Abstract availabl

Acceptability of the transitional wearable companion “+me” in typical children: a pilot study

This work presents the results of the first experimentation of +me-the first prototype of Transitional Wearable Companion–run on 15 typically developed (TD) children with ages between 8 and 34 months. +me is an interactive device that looks like a teddy bear that can be worn around the neck, has touch sensors, can emit appealing lights and sounds, and has input-output contingencies that can be regulated with a tablet via Bluetooth. The participants were engaged in social play activities involving both the device and an adult experimenter. +me was designed with the objective of exploiting its intrinsic allure as an attractive toy to stimulate social interactions (e.g., eye contact, turn taking, imitation, social smiles), an aspect potentially helpful in the therapy of Autism Spectrum Disorders (ASD) and other Pervasive Developmental Disorders (PDD). The main purpose of this preliminary study is to evaluate the general acceptability of the toy by TD children, observing the elicited behaviors in preparation for future experiments involving children with ASD and other PDD. First observations, based on video recording and scoring, show that +me stimulates good social engagement in TD children, especially when their age is higher than 24 months

Keep focussing: striatal dopamine multiple functions resolved in a single mechanism tested in a simulated humanoid robot

The effects of striatal dopamine (DA) on behavior have been widely investigated over the past decades, with "phasic" burst firings considered as the key expression of a reward prediction error responsible for reinforcement learning. Less well studied is "tonic" DA, where putative functions include the idea that it is a regulator of vigor, incentive salience, disposition to exert an effort and a modulator of approach strategies. We present a model combining tonic and phasic DA to show how different outflows triggered by either intrinsically or extrinsically motivating stimuli dynamically affect the basal ganglia by impacting on a selection process this system performs on its cortical input. The model, which has been tested on the simulated humanoid robot iCub interacting with a mechatronic board, shows the putative functions ascribed to DA emerging from the combination of a standard computational mechanism coupled to a differential sensitivity to the presence of DA across the striatum