MODULATED EXPLORATORY DYNAMICS CAN SHAPE SELF-ORGANIZED BEHAVIOR

Frank Hesse, Ralf Der, J. Michael Herrmann

Research output: Contribution to journalArticlepeer-review

Abstract

We study an adaptive controller that adjusts its internal parameters by self-organization of its interaction with the environment. We show that the parameter changes that occur in this low-level learning process can themselves provide a source of information to a higher-level context-sensitive learning mechanism. In this way, the context is interpreted in terms of the concurrent low-level learning mechanism. The dual learning architecture is studied in realistic simulations of a foraging robot and of a humanoid hand that manipulated an object. Both systems are driven by the same low-level scheme, but use the second-order information in different ways. While the low-level adaptation continues to follow a set of rigid learning rules, the second-order learning modulates the elementary behaviors and affects the distribution of the sensory inputs via the environment.

Original languageEnglish
Pages (from-to)273-291
Number of pages19
JournalAdvances in Complex Systems
Volume12
Issue number3
Publication statusPublished - Jun 2009

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