Essay Abstract
The loosely defined concept of a pattern seems to provide a fruitful framework for approaching some of the questions about limits on what can be known about the real world. Nature comes in patterns, and patterns can also be studied in their own right, merely as patterns. We will draw a distinction between patterns in Nature and patterns in the abstract, and broaden it to a partial characterization of science and mathematics. Then we introduce a partial taxonomy of pattern types and notice that the various limitative theorems of mathematical logic severely constrain what can be known using algorithmic mathematical patterns, but are not necessarily pertinent to other, non-algorithmic, types of patterns. Next we will use the concept of Free Will to question whether human cerebration is algorithmic. This appears to open the door to a possibility that if human cerebration is non-algorithmic, perhaps we can know the world more completely than the limitative theorems would seem to imply. However, knowing the world would involve knowing what mathematical pattern Nature has chosen, so to speak, for various natural phenomena. That seems to be impossible because, having only finitely many empirical data points about Nature, there should be an intractably large infinity of mathematical patterns that fit the data. Is there a way to cut down on this infinite set? My conjecture is that there is no adequate way, which sounds pessimistic at first blush, but seems to me to be actually quite an optimistic assessment of the path forward.
Author Bio
I graduated from MIT in mathematics almost half a century ago, moved to Vermont to ski, started a school for ski racers (Green Mountain Valley School) and a string of other small businesses. My current business is Super Thin Saws.