28,698 research outputs found
Introduction: The Third International Conference on Epigenetic Robotics
This paper summarizes the paper and poster contributions
to the Third International Workshop on
Epigenetic Robotics. The focus of this workshop is
on the cross-disciplinary interaction of developmental
psychology and robotics. Namely, the general
goal in this area is to create robotic models of the
psychological development of various behaviors. The
term "epigenetic" is used in much the same sense as
the term "developmental" and while we could call
our topic "developmental robotics", developmental
robotics can be seen as having a broader interdisciplinary
emphasis. Our focus in this workshop is
on the interaction of developmental psychology and
robotics and we use the phrase "epigenetic robotics"
to capture this focus
Beyond Gazing, Pointing, and Reaching: A Survey of Developmental Robotics
Developmental robotics is an emerging field located
at the intersection of developmental psychology
and robotics, that has lately attracted
quite some attention. This paper gives a survey of
a variety of research projects dealing with or inspired
by developmental issues, and outlines possible
future directions
A Unified Model For Developmental Robotics
We present the architecture and distributed
algorithms of an implemented system called
NeuSter, that unifies learning, perception and action
for autonomous robot control. NeuSter comprises
several sub-systems that provide online
learning for networks of million neurons on machine
clusters. It extracts information from sensors,
builds its own representations of the environment
in order to learn non-predefined goals
Developmental Robotics from Developmental Psychology
Developmental robotics is concerned with the
design of algorithms that promote robot adaptation
and learning through qualitative growth of
behaviour and increasing levels of competence.
This paper uses ideas and inspiration from psychological
knowledge of pre-grasping infants (up
to 3 months of age) to examine the issues and
factors that might produce similar mechanisms
for use in robotic systems. The study includes
discussion of results from robotic experiments on
sensory-motor models and key issues are raised
throughout
Can Developmental AIS Provides Immunity to a Multi-cellular Robotics System?
The major challenge to multi-cellular robotics system is how to ensure the system is homeostatically stable. This position paper pro- poses a developmental artificial immune system (dev-AIS) framework that tries to provide and maintain homeostasis to the multi-cellular robotics system. If immunity is defined as the ability to maintain home- ostasis; the dev-AIS framework will be designed based on the under- standing and the abstraction of how different organisms attain for this property through evolution and developmental process. Early form of In- nate Immunity evolve from the predator-and-anti prey relationship of the single-celled organism. Progress in evolution drove the evolution of im- munity from this simple relationship to the development of the immune system in multi-cellular organisms
Intrinsic Motivation Systems for Autonomous Mental Development
Exploratory activities seem to be intrinsically rewarding
for children and crucial for their cognitive development.
Can a machine be endowed with such an intrinsic motivation
system? This is the question we study in this paper, presenting a number of computational systems that try to capture this drive towards novel or curious situations. After discussing related research coming from developmental psychology, neuroscience, developmental robotics, and active learning, this paper presents the mechanism of Intelligent Adaptive Curiosity, an intrinsic motivation system which pushes a robot towards situations in which it maximizes its learning progress. This drive makes the robot focus on situations which are neither too predictable nor too unpredictable, thus permitting autonomous mental development.The complexity of the robotâs activities autonomously increases and complex developmental sequences self-organize without being constructed in a supervised manner. Two experiments are presented illustrating the stage-like organization emerging with this mechanism. In one of them, a physical robot is placed on a baby play mat with objects that it can learn to manipulate. Experimental results show that the robot first spends time in situations
which are easy to learn, then shifts its attention progressively to situations of increasing difficulty, avoiding situations in which nothing can be learned. Finally, these various results are discussed in relation to more complex forms of behavioral organization and data coming from developmental psychology.
Key words: Active learning, autonomy, behavior, complexity,
curiosity, development, developmental trajectory, epigenetic
robotics, intrinsic motivation, learning, reinforcement learning,
values
Development of artificial empathy
AbstractWe have been advocating cognitive developmental robotics to obtain new insight into the development of human cognitive functions by utilizing synthetic and constructive approaches. Among the different emotional functions, empathy is difficult to model, but essential for robots to be social agents in our society. In my previous review on artificial empathy (Asada, 2014b), I proposed a conceptual model for empathy development beginning with emotional contagion to envy/schadenfreude along with self/other differentiation. In this article, the focus is on two aspects of this developmental process, emotional contagion in relation to motor mimicry, and cognitive/affective aspects of the empathy. It begins with a summary of the previous review (Asada, 2014b) and an introduction to affective developmental robotics as a part of cognitive developmental robotics focusing on the affective aspects. This is followed by a review and discussion on several approaches for two focused aspects of affective developmental robotics. Finally, future issues involved in the development of a more authentic form of artificial empathy are discussed
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