Some interesting ideas. He points out that cognitive science is young and can be multi-paradigmatic, and is clear that this is non-mainstream cognitive science. It is an attempt to explain cognition without involving appeals to mental gymnastics on mental representations of the world: the world is its own model.

"The term radical embodied cognition is from Andy Clark, who defines it as follows: Thesis of Radical Embodied Cognition[:] Structured, symbolic, representational, and computational views of cognition are mistaken. Embodied cognition is best studied by means of noncomputational and nonrepresentational ideas and explanatory schemes, involving, e.g., the tools of Dynamical Systems theory."

"...antirepresentationalism (which implies anticomputationalism) is the core of radical embodied cognitive science."

There's a long discussion of Randall Beer's 2003 paper "The Dynamics of Active Categorical Perception in an Evolved Model Agent" that uses a continuous time, real-valued neural network (CTRNN). https://www.cs.swarthmore.edu/~meeden/DevelopmentalRobotics/... "Using the model of the CTRNN alone, one can only tell how an instantaneous input will affect a previously inactive network. But because the network is recurrent, the effect of any instantaneous input to the network will be largely determined by the network’s background activity when the input arrives, and that background activity will be determined by a series of prior inputs. This model of the CTRNN, in other words, is informative only if one knows what flow of prior inputs to the neural network typically precedes (and so determines the typical background activity for) a given input. The impact of the visual stimulus is determined by prior stimuli and the behavioral response to those prior stimuli. The model of the CTRNN is useful, that is, only when combined with the models of the whole coupled system and the agent–environment dynamics. These three dynamical systems compose a single tripartite model. ...The models also show that the agent’s "knowledge" does not reside in its evolved nervous system. The ability to categorize the object as a circle or a diamond requires temporally extended movement on the part of the agent, and that movement is driven by the nature and location of the object as well as the nervous system. To do justice to the knowledge, one must describe the agent’s brain, body, and environment. Notice that none of these dynamical models refers to representations in the CTRNN in explaining the agent’s behavior. The explanation is of what the agent does (and might do), not of how it represents the world. This variety of explanation—of the agent acting in the environment and not of the agent as representer—is a common feature of dynamical modeling..."