Most theories of the mind assume that the mind is simple, meaning that the same kind of rules apply to the entire set of mind-related predicates. This is the case for computational models and connectionist systems, and this is the case for many verbal descriptions. Complex systems (such as high dimensional nonlinear dynamical systems) certainly cannot be considered simple in the above-stated sense. Much as Putnam’s “open systems”, they can support many different kinds of rule sets. I discuss some of the implications of the nature of complex systems for the theory of mind.

Evolution is more than just adaptation and selection - these, taken alone, would not produce an open-ended development, as seen from present-day evolutionary simulations. Based on considerations from causality, a new model is developed, which allows for a dynamic extension of the selection forces that are active at a given moment. In this way a sustained evolutionary process may become possible. I present both the theory and some first simulation results. Reference: www.jaist.ac.jp/~g-kampis/EvoTech/Towards.html

It is a commonplace saying that Nature is not split up into departments. On this basis, interdisciplinarity should be the rule, rather than the exception, yet in most cases it stops at the level of a cooperation between closely related disciplines, such as in the case of physical chemistry or microbiology, which are interdisciplinary in a narrow sense: they work together. Now there is a different sense, in which even the distant discipines are linked, and that is the patterns and modes of thought followed by them. In this broader sense, interdisciplinarity is something like philosophy, or a search for a meta-theory or, in any case, a common methodology of all (or at least many) scientific enterprises. As such, interdisciplinarity is a close relative of system science (which is largely gone) and philosophy of science (which is raising). But is it meaningful to consider interdisciplinarity so broadly?

This talk is by a person who started out in engineering, converted into system science, has done a PhD in theoretical biology; and presently, some twenty years after first begginnings, works in the fields of philosophy of mind, animal cognition and complex systems, while teaching philosophy of science and related topics. This example, my own example shows that there are topics, problems, methods, and views that connect many fields in the above, encompassing sense. Then, my point, put simply, is this: there is a fundamental unity within human knowledge, and it is best expressed through a biological view of cognition. This unity can be best approached via evolution theory and the study of complex systems, these being the building blocks, that pave the road to the understanding of the cognitive faculties of the organism.

In the talk I will briefly characterize human knowledge as a certain species of animal knowledge, and I will explain why I believe that the study of man as an animal is a key factor to the understanding of the unity of science, broadly construed. Then I am turning towards a discussion of the developing view of the theory of evolution, and that of complex systems, and towards the problem of how they contribute to the issues I raised here.

Dynamic models of the mind enjoy recent popularity and promise to converge to brain models. Yet dynamics, if understood as a single set of equations, or as behavior generated by a single rule system, is too narrow for both. Causal systems are more complex than that: they can support multiple dynamics that changes over time so that one system is always replaced by another. I discuss the relevance of this idea for cognition, together with some of the evidence that supports the existence of related systems in the mind and in the brain.