Show Reference: "Distributed Adaptive Control: A theory of the Mind, Brain, Body Nexus"

Distributed Adaptive Control: A theory of the Mind, Brain, Body Nexus Biologically Inspired Cognitive Architectures, Vol. 1 (July 2012), pp. 55-72, doi:10.1016/j.bica.2012.04.005 by Paul F. M. J. Verschure
    abstract = {Distributed Adaptive Control ({DAC}) is a theory of the design principles underlying the Mind, Brain, Body Nexus ({MBBN}) that has been developed over the last 20 years. {DAC} assumes that the brain maintains stability between an embodied agent and its environment through action. It postulates that in order to act, or know how, the brain has to answer four fundamental questions: why, what, where, when. Thus the function of the brain is to continuously solve the, so called, {H4W} problem. The {DAC} theory is expressed as a robot based neural architecture organized in two complementary structures: layers and columns. The organizational layers are called: reactive, adaptive and contextual and its columnar organization defines the processing of states of the world, the self and the generation of action. Each layer is described with respect to its key hypotheses, implementation and specific benchmarks. After this overview of the key elements of {DAC}, the mapping of its key assumptions towards the invertebrate and mammalian brain is described. In particular, this review will focus on the systems involved in realizing the core principles underlying the reactive layer: the allostatic control of fundamental behavior systems in the vertebrate brain and the emergent non-linearity through neuronal mass action in the locust brain. The adaptive layer will be analyzed in terms of the classical conditioning paradigm and its neuronal substrate the amygdala-cerebellum-neocortex complex together with episodic memory and the formation of sense-act couplets in the hippocampus. For the contextual layer the ability of circuits in the prefrontal cortex to acquire and express contextual plans for action is described. The general overview of {DAC}'s explanation of {MBBN} is combined by examples of application scenarios in which {DAC} has been validated including mobile and humanoid robots, neurorehabilitation and the large-scale interactive space Ada. After 20 years of research {DAC} can be considered a mature theory of {MBBN}. It has build up a track record of explaining core aspects of mind, brain and behavior, has made testable and verified predictions at the level of behavior, physiology and anatomy, has been shown to be able to control complex real-world artefacts and has been successfully applied to brain repair and neurorehabilitation. Currently {DAC} is extended to capture the phenomenon of consciousness, the ultimate challenge in the study of the Mind, Brain, Body Nexus.},
    author = {Verschure, Paul F. M. J.},
    doi = {10.1016/j.bica.2012.04.005},
    issn = {2212683X},
    journal = {Biologically Inspired Cognitive Architectures},
    keywords = {cognitive-model},
    month = jul,
    pages = {55--72},
    posted-at = {2012-10-01 15:42:25},
    priority = {2},
    title = {Distributed Adaptive Control: A theory of the Mind, Brain, Body Nexus},
    url = {},
    volume = {1},
    year = {2012}

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Verschure argues that models of what he calls the mind, brain, body nexus should particularly account for data about the behavior at the system level, ie. overt behavior. He calls this convergent validation

In Verschure's concept of convergent validation, the researcher does not seek inspiration for but constraints for falsification or validation of models in nature.

Mommy, where do models come from?

Verschure champions his model of Distributed Adaptive Control as a model comprising all aspects of the mind, brain, body nexus.

Verschure states his Distributed Adaptive Control (DAC) provides a solution to the symbol grounding problem.

The state spaces in the formal definition of Verschure's DAC already seems to comprise symbols.

Verschure states his is an early model in the tradition of what he calls the "predictive brain" hypothesis and relates it to Friston's free energy principle and Kalman filtering.

Distributed Adaptive Control is a system that can learn sensory-motor contingencies

Verschure explains that, in his DAC system, the contextual layer overrules the adaptive layer as soon as it is able to predict perception well enough.

One version of DAC uses SOMs.

Verschure says neurons don't seem to multiply. Gabbiani et al. say they might.

Verschure summarizes version VII of his distributed adaptive control model as "a unifying theory" of perception cognition, and action. He states that it uses a learned world model in its contextual layer which biases perception processing (top-down) on the one hand, and saliency (bottom-up) on the other. Between these to appears to be what he calls the validation gate which defines matching and mismatch between world model and percepts.