Developmental robotics: Difference between revisions

Revision as of 09:42, 29 January 2015

Revision as of 09:41, 5 May 2015

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{{Use mdy dates|date=October 2014}}

'''Developmental Robotics''' (DevRob), sometimes called '''[[epigenetics|epigenetic]] robotics''', is a scientific field which aims at studying the developmental mechanisms, architectures and constraints that allow lifelong and open-ended learning of new skills and new knowledge in embodied [[machine|machines]]s. As in human children, [[learning]] is expected to be cumulative and of progressively increasing complexity, and to result from self-exploration of the world in combination with [[social relation|social interaction]]. The typical methodological approach consists in starting from theories of human and animal development elaborated in fields such as [[developmental psychology]], [[neuroscience]], [[developmental biology|developmental]] and [[evolutionary biology]], and [[linguistics]], then to formalize and implement them in robots, sometimes exploring extensions or variants of them. The experimentation of those models in robots allows researchers to confront them with reality, and as a consequence developmental robotics also provides feedback and novel hypothesis on theories of human and animal development.

Developmental robotics is related to, but differs from, [[evolutionary robotics]] (ER). ER uses populations of robots that evolve over time, whereas DevRob is interested in how the organization of a single robot's control system develops through experience, over time.

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The sensorimotor and social spaces in which humans and robot live are so large and complex that only a small part of potentially learnable skills can actually be explored and learnt within a life-time. Thus, mechanisms and constraints are necessary to guide developmental organisms in their development and control of the growth of complexity. There are several important families of these guiding mechanisms and constraints which are studied in developmental robotics, all inspired by human development:

# Motivational systems, generating internal reward signals that drive exploration and learning, which can be of two main types:

#* extrinsic motivations push robots/organisms to maintain basic specific internal properties such as food and water level, physical integrity, or light (for e.g. in phototropic systems);

#* intrinsic motivations push robot to search for novelty, challenge, compression or learning progress per se, thus generating what is sometimes called curiosity-driven learning and exploration, or alternatively active learning and exploration;

#Social guidance: as humans learn a lot by interacting with their peers, developmental robotics investigates mechanisms which can allow robots to participate to human-like social interaction. By perceiving and interpreting social cues, this may allow robots both to learn from humans (through diverse means such as imitation, emulation, stimulus enhancement, demonstration, etc. ...) and to trigger natural human pedagogy. Thus, social acceptance of developmental robots is also investigated;