In this draft paper, Fabio Boschetti and I<John Symons> address two questions: First, what is the smallest number of components a computational system needs in order to display genuine novelty? And second, can the novel features of such systems also exhibit novel causal powers? We’d be very grateful for any comments or criticism. The paper is herevia Novel properties generated by interacting computational systems: A minimal model « Objects and Arrows.

After reading John Symons and Fabio Boschetti draft paper I found myself thinking about some things:

• Isn’t this model with the two machines and one IIM similar in some way to what optimization research has done with genetic algorithms (GA)? Or, aren’t genetic algorithms an example of this? If we take a careful look, a chromosome in a GA is something that maps its genome to itself behaving like a machine, and is subject to two (usually two) external interaction openness: crossover with another chromosome to produce a new population, and mutation to random change some of its genes.   These operators would then play the role of the interactive identity machine (IMM). It’s curious that GAs end up being so similar but have been studied under an optimization framework.
• Other aspect that caught my mind is the problem of using an alphabet or memory positions as in machine D. This is something that in CS is natural as it’s represents the obvious pass by value vs. pass by reference. In CS practice each has its merits but it’s interesting to see this reflected in the paper.
• The previous bullet remembers me the need of building agents with operations as generic as they can be… Imagine swap(int, int). It’s probably better to have swap(Obj, Obj) as in this case you might end having a generic operator that will allow your agents to face unknown situations, even if you only work with ints…