Meta-Morphogenesis: Evolution of mechanisms for producing minds
OR
Evolution, development and learning, producing new mechanisms
of evolution, development and learning.
Tuesday 8th May 2012, 5.30 pm
Auditorium Lounge in Robinson College;
This document is
http://www.cs.bham.ac.uk/research/projects/cogaff/misc/cucats-abstract.html
A partial index of discussion notes is in http://www.cs.bham.ac.uk/research/projects/cogaff/misc/AREADME.html
I'll present an idea, that could help to bring different kinds of research together in fruitful cooperation. The idea is that many of the developments in biological evolution that are so far not understood, and in some cases have gone unnoticed, were concerned with changes in information processing. The same is true of changes in individual development and learning: they often produce new forms of information processing. Examples include: learning new ways to learn development of new forms of development evolution of new types of evolution evolution of new types of learning evolution of new forms of development development of new forms of learning how new forms of learning support new forms of evolution .... .... and ways in which social cultural evolution add to the mix Many of the changes escape notice because people assume that what organisms can do is obvious and all that is needed is to explain how it is done. Then explanations and models are produced that turn out seriously inadequate. Alan Turing's work on morphogenesis (see below) explored how micro-interactions in physicochemical structures might account for global transformations from a fertilized egg to an animal or plant, within a single organism. I'll outline a rudimentary theory of "meta-morphogenesis" that aims to show how, over generations, interactions between changing environments, changing animal morphology, and previously evolved information-processing capabilities might combine to produce increasingly complex forms of "informed control", initially just control of physical behaviour, then later also informed control of information-processing. This potentially explains philosophically puzzling features of animal (including human) minds, including the existence of "qualia". It is also related to the transformation of empirical knowledge into a "generative" or "deductive" form, a process labelled "Representational Redescription" by Annette Karmiloff-Smith[*]. I suspect that such processes provide the foundation for human mathematical competences. This defines a research programme, that should help us understand how much more remains to be done if we wish to explain how human and animal minds work, or produce machines rivalling biological intelligence. (No robot comes close, at present.) A key assumption is that in order to understand any kind of mind we need to explore the space of possible minds, and the multifarious requirements they need to satisfy. This is a very difficult task, since many of the requirements are unobvious and depend on unobvious features of the environment. Understanding the requirements requires a deep understanding of relevant features of the environment. Many of those features change over evolutionary time scales and in some cases more rapidly. External influences on development of human minds in most countries are now very different from what they were a few decades ago. Much current research in AI/Robotics, psychology, neuroscience and biology assumes that the main function of brains is to control movement. In contrast I'll argue that there's a wide variety of types of control and some the forms of control that evolved later have very little to do with control of movement, though many of those are related to understanding what kinds of structures and processes can and cannot exist in the world. But understanding the environment need not be motivated by a need to produce or prevent motion. Later developments, such as the development of mathematical and philosophical investigations are even more remote from any requirement to produce motion, even if some of them were originally provoked by problems of coping with a complex environment.
For information about the society and arrangements for the talk, please contact: cucats-executive[AT]srcf.ucam.org
Perhaps one day, with far greater computing power than Turing had available, we shall be ableThe 'wave' theory which has been developed here depends essentially on the assumption that the reaction rates are linear functions of the concentrations, an assumption which is justifiable in the case of a system just beginning to leave a homogeneous condition. Such systems certainly have a special interest as giving the first appearance of a pattern, but they are the exception rather than the rule. Most of an organism, most of the time, is developing from one pattern into another, rather than from homogeneity into a pattern. One would like to be able to follow this more general process mathematically also. The difficulties are, however, such that one cannot hope to have any very embracing theory of such processes, beyond the statement of the equations. It might be possible, however, to treat a few particular cases in detail with the aid of a digital computer. This method has the advantage that it is not so necessary to make simplifying assumptions as it is when doing a more theoretical type of analysis. It might even be possible to take the mechanical aspects of the problem into account as well as the chemical, when applying this type of method. The essential disadvantage of the method is that one only gets results for particular cases. But this disadvantage is probably of comparatively little importance. Even with the ring problem, considered in this paper, for which a reasonably complete mathematical analysis was possible, the computational treatment of a particular case was most illuminating. The morphogen theory of phyllotaxis, to be described, as already mentioned, in a later paper, will be covered by this computational method. Non-linear equations will be used. It must be admitted that the biological examples which it has been possible to give in the present paper are very limited. This can be ascribed quite simply to the fact that biological phenomena are usually very complicated. Taking this in combination with the relatively elementary mathematics used in this paper one could hardly expect to find that many observed biological phenomena would be covered. It is thought, however, that the imaginary biological systems which have been treated, and the principles which have been discussed, should be of some help in interpreting real biological forms.
But it may turn out that we need new kinds of computing machinery, including perhaps chemical computers.
The abstract for a related conference presentation is available here:
http://www.cs.bham.ac.uk/research/projects/cogaff/misc/pt-ai-abstract.html
A messy, growing, collection of discussion notes on
meta-morphogenesis is here:
http://www.cs.bham.ac.uk/research/projects/cogaff/misc/meta-morphogenesis.html
Also accessible as:
http://tinyurl.com/M-M-Gen
Related to Karmiloff-Smith's ideas in this very personal review of "Beyond Modularity":
http://www.cs.bham.ac.uk/research/projects/cogaff/misc/beyond-modularity.html
For more on qualia see this presentation.
PDF presentations exploring some of the ideas behind this talk can be found
here:
http://www.cs.bham.ac.uk/research/projects/cogaff/talks/
Further theoretical background material on philosophical and computational issues,
including discussion of
varieties of architectures for minds, and some empirical observations can be found in
The CogAff Project Web Site
Discussion notes.
Maintained by
Aaron Sloman
School of Computer Science
The University of Birmingham