Show jumping: Real Algorithm

vlopez's picture

           
 
            On last week’s discussion group, we were discussing the concept of algorithms as presented by Daniel Dennett in his book Darwin’s Dangerous Idea: Evolution and the Meanings of Life. We discussed various examples of algorithms, such as Dennett’s example of the tennis tournament and Dennet’s depiction of algorithms as “substrate neutral”. After a long discussion as to what substrate neutrality meant and what exactly was an algorithm and if it was applicable to daily-life examples, we still found ourselves in an abyss. With this paper, I will try to bring in a daily-life example to help illustrate the concept of algorithms, as described by Dennett, in a more concrete manner.
 
            The example I chose to present as an explanation of the concept of an algorithm is show jumping. Show jumping has been part of my life for fifteen years now, so I know it well and feel that it will be a satisfactory example for explaining the confusion that has been raised in class.
 
            Dennett defines algorithms as “simple, straight-forward steps that are part of a logical structure, that when followed correctly will yield guaranteed results.” (Dennett 50-51) It is in other words, “a foolproof recipe” (Dennett 51). Show jumping has a very basic recipe for success: get to the jump at the correct distance and you are guaranteed a clear jump. 
 
            First, let me explain how show jumping works. It is an individual sport, in which you are in a ring with a horse, with the objective of going through the course without knocking any jumps down. Pretty simple right? But in order to clear a jump, you must go through a series of steps. First you start to canter, then you look at the jump you want to take, and once you are headed for the jump you have to measure the distance for the horse to jump. The distance is the spot from where you want to take-off so the horse has enough space that he can pick up its front legs, but it should not be big enough so as the horse has the option of refusing the jump. If you start off with good rhythm, center the horse and find the correct distance, you are guaranteed a clear jump. 
 
            So far, show jumping is looking like a fool-proof recipe. But what does it mean that it is a substrate neutral algorithm? As discussed in class, if you have a tennis tournament divided up into brackets, there will inevitably be a winner and a loser regardless of who you put in it. The substrate neutrality refers to the logic behind the process, not on the subjects taking part in the logical process. Some may argue that this would not apply to show jumping. What if you follow the algorithmic steps correctly but the horse just didn’t feel like jumping that day and refused the jump? This would veto the depiction of show jumping as an algorithmic process. This is a random occurrence that can, indeed, affect the outcome of the process, but it in itself is not part of the algorithmic process because it is unpredictable or random. Dennett uses the example of the stock market motto: “Buy low, sell high”. Anyone who follows this should and would be rich, but the problem is that the market is so random that we don’t know when it is going to be low or high. Therefore, you can follow the motto (algorithmic process), but the randomness of the stock market can alter the expected outcome, in this case, cashing in. This is the same in show jumping; the recipe is correct and will work effectively, but random factors such as the horse’s temperament might influence the outcome. 
 
            I have hopefully provided a good depiction of a daily-life algorithmic process in a way that may be more approachable and understandable. Now that we can grab a hold of the idea of an algorithmic process, I invite you to explore and look around you and question if everything can be an algorithmic process. We perform basic steps every day, like making a bed or driving, but are these algorithmic processes? What exactly determines if a series of basic steps get to be called an ‘algorithmic process’? 
 
Bibliography
Dennett, Daniel C. Darwin's Dangerous Idea: Evolution and the Meanings of Life. New York: Simon & Schuster Paperbacks, 1995.
 

Comments

vlopez's picture

big response

I guess you could  say that the search for God could be considered an algorithmic process even though I still would not be able to put a "recipe-like" depiction on HOW to find God.  With these past two papers I do seem to want to rely only on certainty.  It is true, I do like to have a certain idea of what is going to happen, but at the same time I do like to welcome unpredictable changes... they make life more fun!  I like to think of these random occurrences as unexpected events that bring out more of yourself or a situation- good or bad - that you did not know was in you or was capable of happening.  That said, I welcome randomness! But at the same time there is a need to hold on to something - anything - that can allow a sense of control.  This may be why I have been trying to find tangible 'things' to hold on to. Whilst they may give me a sense of control, I am fully aware of life's unpredictability and have learned to accept it.  That said, I don't think randomness in 'algorithmic processes' as described in this essay would necessarily negate the processes' reliability; it's simply a bump in the road - or continuing from the examples above, an unexpected refusal from your horse - which can be dealt with.  And in any case, that's why we get more opportunities throughout life.

Anne Dalke's picture

On randomness

vlopez--
I'm thinking right now about the connections between your last essay, on The Quest for Truth, and this one, on the search for a good illustration of a “logical structure that will yield guaranteed results." Do the two projects seem related to you? If so, might the questions w/ which you end here become even larger ones? If "everything can be an algorithmic process," might that include the search for God?

I guess my other "big" question has to do with whether, taken together, these two essays testify to your own search for structures of certainty: for that which is reliable, in sharp contrast (say) to Paul's valorization of the unpredictable and random. Are the stories you are telling offered as counters to those he narrates? How might the two accounts of the operation of the universe operate in relation to one another?

What I'm really asking is not just--as you do--"What exactly determines if a series of basic steps get to be called an ‘algorithmic process’?" but also --along with phyllobates--what happens if the algorithmic process includes random factors (as your example acknowledges it does)? Does that negate or reinforce its reliability for you? Does that negate or reinforce the unpredictability of the universe for you?

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