The rate distortion manifold is considered as a carrier for elements of the theory of information proposed by C. E. Shannon combined with the semantic precepts of F. Dretske’s theory of communication. This type of information space was suggested by R. Wallace as a possible geometric–topological descriptive model for incorporating a dynamic information based treatment of the Global Workspace theory of B. Baars. We outline a more formal mathematical description for this class of information space and further clarify its structural content and overall interpretation within prospectively a broad range of cognitive situations that apply to individuals, human institutions, distributed cognition and massively parallel intelligent machine design. Povzetek: Predstavljena je formalna definicija prostora za opisovanje kognitivnih procesov. 1

Biological organisms display an amazing ability during their ontogenetic development to adaptively develop solutions to the various problems of survival that their environments present to them. Dynamical and embodied models of cognition are beginning to o#er new insights into how the numerous, heterogeneous elements of neural structures may self-organize during the development of the organism in order to e#ectively form adaptive categories and increasingly sophisticated skills, strategies and goals. The ontogenetic development of behavior in biological organisms represents a significant level of improvement over current approaches to machine learning.

Biological organisms display an amazing ability during their ontogenetic development to adaptively develop solutions to the various problems of survival that their environments present to them. Dynamical and embodied models of cognition (Clark, 1997; Edelman & Tononi, 2000; Franklin, 1995; Freeman, 1999a, 1999b; Freeman & Kozma, 2000; Freeman, Kozma, & Werbos, 2000; Hendriks-Jansen, 1996; Kelso, 1995; Kozma & Freeman, 2001; Port & van Gelder, 1995; Skarda & Freeman, 1987; Thelen & Smith, 1994) are beginning to offer new insights into how the numerous, heterogeneous elements of neural structures may self-organize during the development of the organism in order to effectively form adaptive categories and increasingly sophisticated skills, strategies and goals. In this paper we present models of ontogenetic development built on neurologically inspired, bottom-up, dynamic approaches to embodied category formation such as those done by Freeman (1975, 1999b), Freeman and Kozma (2000), Kozma and Freeman (2001), Verschure (1998) and Edelman (1987, 1989). We believe that building on such mechanisms from an embodied dynamical perspective will produce autonomous agents that display greatly increased flexibility in their behavior. Such models will represent a better understanding of how the brains of biological organisms not only form perceptual categories of their environments during development, but also develop effective patterns of behavior through the dynamic self-organization of neurological patterns of activity.

The development of complex, adaptive behavior in biological organisms represents vast improvement over current methods of learning for artificial autonomous systems. Dynamical and embodied models of cognition [1-13] are beginning to provide new insights into how the chaotic, non-linear dynamics of heterogeneous neural structures may self-organize in order to develop e ective patterns of behavior. We are interested in creating models of ontogenetic development that capture some of the exibility and power of biological systems. In this paper we present a testbed for the creation and testing of models of development.

The belief that conscious will is merely ‘‘an illusion created by the brain’ ’ appears to be gaining in popularity among cognitive neuroscientists. Its main adherents usually refer to the classic, but controversial ‘Libet-experiments’, as the empirical evidence that vindicates this illusion-claim. However, based on recent work that provides other interpretations of the Libet-experiments, we argue that the illusion-claim is not only empirically invalid, but also theoretically incoherent, as it is rooted in a category mistake; namely, the presupposition that neuronal activity causes conscious will. We show that the illusion-claim is based on the behaviorist ‘input-output ’ paradigm, and discuss the notions of ‘self-organization ’ and ‘self-steering ’ to provide an alternative perspective on the causal efficacy of conscious will. In the final sections, a tentative theoretical picture is sketched of conscious will as an instance of self-steered self-organization. We conclude that the subjective experience of conscious will is not a misguided one, but rather that the mechanisms supporting conscious will are considerably more complex than mainstream cognitive neuroscience currently acknowledges. Keywords: Conscious Will; Benjamin Libet; Self-Organization 1.