Multi-agent platform for development of educational games for children with autism

Multi-agent system of autonomous interactive blocks that can display its active state through color and light intensity has been developed. Depending on the individual rules, these autonomous blocks could express emergent behaviors which are a basis for various educational games. The multi-agent system is used for developing games for behavioral training of autistic children. This paper features the functional and electronic design of the individual blocks and transformation of the multi-agent system to a platform that allows multiple games to be designed through easy reprogramming of the blocks. Three game concepts that show the type of games that can easily be implemented and reprogrammed are described. The impact of this platform is shortly mentioned in the discussion. The initial tests of using the platform for various educational games are very positive. However, the results of user tests go beyond the scope of this paper and are not discussed in the text that follows

Using an emergent system concept in designing interactive games for autistic children

This paper features the design process, the outcome, and preliminary tests of an interactive toy that expresses emergent behavior and can be used for behavioral training of autistic children, as well as for an engaging toy for every child. We exploit the interest of the autistic children in regular patterns and order to stimulate their motivational, explorative and social skills. As a result we have developed a toy that consists of undefined number of cubes that express emergent behavior by communicating with each other and changing their colors as a result of how they have been positioned by the players. The user tests have shown increased time of engagement of the children with the toy in comparison with their usual play routines, pronounced explorative behavior and encouraging results with improvement of turn taking interaction

Spatial Navigation Based on Novelty Mediated Autobiographical Memory

Abstract. This paper presents a method for spatial navigation performed mainly on past experiences. The past experiences are remembered in their temporal context, i.e. as episodes of events. The learned episodes form an ac-tive autobiography that determines the future navigation behaviour. The epi-sodic and autobiographical memories are modelled to resemble the memory formation process that takes place in the rat hippocampus. The method im-plies naturally inferential reasoning in the robotic framework that may make it more flexible for navigation in unseen environments. The relation between novelty and life-long exploratory (latent) learning is shown to be important and therefore is incorporated into the learning process. As a result, active au-tobiography formation depends on latent learning while individual trials might be reward driven. The experimental results show that learning mediat-ed by novelty provides a flexible and efficient way to encode spatial informa-tion in its contextual relatedness and directionality. Therefore, performing a novel task is fast but solution is not optimal. In addition, learning becomes naturally a continuous process- encoding and retrieval phase have the same underlying mechanism, and thus do not need to be separated. Therefore, building a “life long ” autobiography is feasible.

Sensorimotor paradigms for design of movement and social interaction

The human brain has evolved for governing motor activity by transforming sensory patterns to patterns of motor coordination. Movement, as a basic bodily expression of this governing function is shown to underlie higher cognitive processes and social interaction.There are three prevailing concepts of sensorimotor interaction that set up different frameworks for design of artificial movement. This paper focuses on the common coding [1??] paradigm of sensorimotor interaction as justified by recent experimental studies on the mirror neuron system. It aims to provide a novel approach to design of movement interactions in an inter-agent setting

Robots for social training of autistic children : empowering the therapists in intensive training programs

We apply a participatory co-creation process to empower health researchers/practitioners with robot assistants or mediators in behavioral therapies for children with autism. This process combines (a) a user centered design of a platform to support therapists to create and share behavioral training scenarios with robots and (b) acquisition of domain specific knowledge from the therapists in order to design robot-child interaction scenarios that accomplish specific learning goals. These two aspects of the process are mutually dependant and therefore require an iterative design of a technological platform that will make gradual steps towards creating optimal affordances for therapists to create robot-mediated scenarios to the best of the technical capabilities of the robot, i.e. through co-creation. For this purpose an end-user programming environment augmented with learning by demonstration tool and textual commands is being developed. The initial tests showed that this tool can be used by the therapists to create own training scenarios with existing behavioral components. We conclude that this platform comply with the needs of the contemporary practices that focus on personalization of the training programs for every child. In addition, the proposed framework makes possible to include extensions to the platform for future developments

Emotion recognition in robots in a social game for autistic children

This paper provides a framcwork for a social game thar has as a goal improvillg the social interaction skilIs through associative play. It describes the design of the game: platform and an ongoing study on the perception of emotional expressioll from morion cues for communication alld social coordination. EspeciaJly, childn:n with autism spectrum disorders are targeled, since they will bendit most from bchavioral training that may improvc their social ski lis. The promising resulls from two stages of this work are shown

Emotion recognition in robots in a social game for autistic children

This paper provides a framcwork for a social game thar has as a goal improvillg the social interaction skilIs through associative play. It describes the design of the game: platform and an ongoing study on the perception of emotional expressioll from morion cues for communication alld social coordination. EspeciaJly, childn:n with autism spectrum disorders are targeled, since they will bendit most from bchavioral training that may improvc their social ski lis. The promising resulls from two stages of this work are shown

Semantics through embodiment: a non-linear dynamics approach to affective design

In this paper we address the creation and interpretation of movements, light and sound from a fundamental and innovative viewpoint. Using a number of concepts from the relatively new and very promising research field of nonlinear adaptive systems, and getting some inspiration from psychophysical studies on the perception of emotion we address the study of movements and other autonomous expressions of products. The goal is to understand the semantics of movement, particularly the emotional meaning of the movement and to translate it to other autonomous expressive behavior

Simulation of sensory integration dysfunction in autism with dynamic neural fields model

This paper applies dynamic neural fields model [1,23,7] to multimodal interaction of sensory cues obtained from a mobile robot, and shows the impact of different temporal aspects of the integration to the precision of movements. We speculate that temporally uncoordinated sensory integration might be a reason for the poor motor skills of patients with autism. Accordingly, we make a simulation of orientation behavior and suggest that the results can be generalized for grasping and other movements that are performed in three dimensional space. Our experiments show that impact of temporal aspects of sensory integration on the precision of movement are concordant with behavioral studies of sensory integration dysfunction and of autism. Our simulation and the robot experiment may suggest ideas for understanding and training the motor skills of patients with sensory integration dysfunction, and autistic patients in particular, and are aimed to help design of games for behavioral training of autistic children