University of New England

The Endogenous Systems Research Group was created to understand self-generating systems, known as self-referential systems. Examples span a range from enzymes, to one-celled organisms, to brains, to mental artifacts such as semantic languages, and even to organizations based on shared mental artifacts, such as social systems. The self generating aspect of such systems is widely enough recognized that in both medicine and economics they are technically referred to as called endogenous systems. The goals of the Endogenous Systems Research Group are to understand the distinguishing features of living things both qualitatively and mathematically and to apply what is learned to the creation of human-made systems having the same properties. A necessary feature that distinguishes living processes from non-living processes is a self-producing organization.

Endogeny captures a fundamental difference between conventional engineering systems and the processes observed in organisms. As engineers seek either to control living systems or to create artificial versions of them, we anticipate that they too will adopt this term.

In the traditional scientific view, the operation of a mechanism unfolds without any particular "purpose" (except perhaps as intended by its creator). In other words, a mechanism is strictly syntactic; it operates in a world of abstract rules without meaning. In contrast, it is clear to most observers of living systems that they do operate with a purpose, one determined by the organism for its own benefit and survival. In other words, an organism necessarily embodies value-laden, or semantic processes.

It is a controversial claim that there is a fundamental difference between conventional engineering systems and the processes observed inside organisms. Nevertheless, semantic processes do not correspond to computable models; attempts to describe semantic ambiguities with algorithms lead to logical paradoxes. This does not mean that endogenous systems cannot be understood. What it does mean, is that the techniques conventionally accessible to engineers are neither adequate nor appropriate.

To understand endogenous systems one must introduce impredicative models. An impredicative mathematical structure is one that is defined by its relationship with itself. Recent discoveries in mathematics, such as hyperset formalism, show that such models are both theoretically legitimate and practically useful. The hypothesized correspondence between endogenous natural systems and impredicative formal systems is one of the objects of investigation by the NEI Endogenous Systems Research Group.

As a matter of immediate practicality, currently Paul Bach-y-Ritam M.D. has successfully demonstrated medical prostheses that non-invasively couple electronically-generated images into the human visual cortex, enabling the blind to "see." NASA Ames is able to couple data from the nervous system into electronics; their research goal is control a spacecraft "by thought." The point is that it is already feasible to non-invasively "wire" a stream of electronically generated symbols directly into and out of the human nervous system.

Longer term, perhaps the most dramatic effects of an understanding of endogenous processes would be in psychology. If abduction could be understood mathematically, then it might serve as the foundation for understanding of human semantic processes. Starting from the question of how data are abstracted sensations, sensations into percepts, and percepts into concepts, an overarching "theory of cognition" might be discovered. This might serve as the basis of answering many of the perplexing questions of human behavior.