Between the earliest proto-organisms and modern complex animals, evolution has produced hugely varied physical forms, physical behaviours, life-cycles, and modes of reproduction. All use information of various kinds (along with matter and energy). Information contents control internal and external processes: including changes through learning and development of individuals, and in genome development by evolution. Information contents are also involved in social and cultural changes. I conjecture that animal intelligence involves far more diversity in forms of information-processing than we have dreamed of so far, and that the sources of that diversity lie in various layers of complexity in the physical, biological, and social environments in which evolution and individual development occur. Contrary to common assumptions about embodiment, some of the more abstract features of the environment (e.g. rigidity and diversity of 3-D terrain structures) can have a common influence on evolution of information-processing in animals with very different neural mechanisms, sensory and motor systems and morphology, though implementations of the common functionality differ. The ontologies currently used for observation and theory-construction by most neuroscientists, psychologists, biologists, and AI/Robotics researchers cannot accommodate all of those features, seriously restricting the explanatory power of theories using current ontologies. I shall address some ways of overcoming those limitations, in part by illustrating environmental features that have received insufficient attention, and in part by decomposing some of the functions of a genome.
The talk will build on ideas in
Jackie Chappell and Aaron Sloman,
Natural and artificial meta-configured altricial information-processing systems,
in Int. J. of Unconventional Computing, vol 3, No 3, 2007 pp. 211--239,
http://www.cs.bham.ac.uk/research/projects/cosy/papers/#tr0609Aaron Sloman,
What's information, for an organism or intelligent machine? How can a machine or organism mean?
In Information and Computation, Eds. G. Dodig-Crnkovic and M. Burgin, World Scientific, 2010,
http://www.cs.bham.ac.uk/research/projects/cogaff/09.html#905Draft PDF slides for presentation can be found at http://www.cs.bham.ac.uk/research/projects/cogaff/talks/#talk89
NOTE:
The use of "information" here is explained in the second reference,
and the causal role of information in virtual machinery is explained
in more detail in
http://www.cs.bham.ac.uk/research/projects/cogaff/talks/#talk86
Supervenience and Causation in Virtual Machinery
Maintained by
Aaron Sloman
School of Computer Science
The University of Birmingham
Last updated: 9 Dec 2010; 24 Dec 2010
Installed: 9 Dec 2010