AUTHOR=Der Ralf TITLE=In Search for the Neural Mechanisms of Individual Development: Behavior-Driven Differential Hebbian Learning JOURNAL=Frontiers in Robotics and AI VOLUME=2 YEAR=2016 URL=https://www.frontiersin.org/journals/robotics-and-ai/articles/10.3389/frobt.2015.00037 DOI=10.3389/frobt.2015.00037 ISSN=2296-9144 ABSTRACT=

When Donald Hebb published his 1949 book “The Organization of Behavior” he opened a new way of thinking in theoretical neuroscience that, in retrospective, is very close to contemporary ideas in self-organization. His metaphor of “wiring” together what “fires together” matches very closely the common paradigm that global organization can derive from simple local rules. While ingenious at his time and inspiring the research over decades, the results still fall short of the expectations. For instance, unsupervised as they are, such neural mechanisms should be able to explain and realize the self-organized acquisition of sensorimotor competencies. This paper proposes a new synaptic law that replaces Hebb’s original metaphor by that of “chaining together” what “changes together.” Starting from differential Hebbian learning, the new rule grounds the behavior of the agent directly in the internal synaptic dynamics. Therefore, one may call this a behavior-driven synaptic plasticity. Neurorobotics is an ideal testing ground for this new, unsupervised learning rule. This paper focuses on the close coupling between body, control, and environment in challenging physical settings. The examples demonstrate how the new synaptic mechanism induces a self-determined “search and converge” strategy in behavior space, generating spontaneously a variety of sensorimotor competencies. The emerging behavior patterns are qualified by involving body and environment in an irreducible conjunction with the internal mechanism. The results may not only be of immediate interest for the further development of embodied intelligence. They also offer a new view on the role of self-learning processes in natural evolution and in the brain. Videos and further details may be found under http://robot.informatik.uni-leipzig.de/research/supplementary/NeuroAutonomy/.