Unified theories of cognition
Adaptive resonance theory (ART)
The handbook of brain theory and neural networks
Connectionist-Symbolic Integration: From Unified to Hybrid Approaches
Connectionist-Symbolic Integration: From Unified to Hybrid Approaches
Field Guide to Dynamical Recurrent Networks
Field Guide to Dynamical Recurrent Networks
Spatiotemporal Connectionist Networks: A Taxonomy and Review
Neural Computation
Synergetic Computers & Cognition
Synergetic Computers & Cognition
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Dynamical system theory offers approaches towards cognitive modeling and computation inspired by self-organization and pattern formation in open systems operating far from thermodynamical equilibrium. In this spirit we propose a functional architecture for the emergence of complex functions such as sequential motor behaviors. We model elementary functions as Structured Flows on Manifolds (SFM) that provide an unambiguous deterministic description of the functional dynamics, while still remaining compatible with the intrinsically low dimensionality of elementary behaviors. Pattern competition processes (operating on a hierarchy of time scales) provide the means to compose complex functions out of simpler constituent ones. Our underlying hypothesis is that complex functions can be decomposed in functional modes (simpler building blocks). Simulations of generating cursive handwriting provide proof of concept and suggest exciting avenues towards extending the current framework to other human functions including learning and language.