Control Theory, Behavior and Evolution
I’ve taken some passages from the newspaper article on the Princeton research to highlight parallels and distinctions with my reading of animal behavior.
“Chakrabarti and Rabitz analyzed these observations of the proteins' behavior from a mathematical standpoint, concluding that it would be statistically impossible for this self-correcting behavior to be random, and demonstrating that the observed result is precisely that predicted by the equations of control theory. By operating only at extremes, referred to in control theory as "bang-bang extremization," the proteins were exhibiting behavior consistent with a system managing itself optimally under evolution.”
## These “extreme states” in NDT would correspond to prey and predator polarities. When two dogs meet and differentiate themselves according to these poles, (which is inevitable because according to the principle of emotional conductivity they will experience extreme friction if they don’t) all the emotional charge they’ve accumulated over the course of their life and which vibrates as their “personality” can eventually smooth out into a wave function, (dogs playing and mounting) and then evolves into what we recognize as an emotional bond. Now this energy has been harnessed and moreover is a source of information (deflected onto a midpoint) that can be applied to overcome more and more formidable forms of resistance (group of wolves breaking down a herd defense) and thereby add new energy to the system. ##
“The scientists do not know how the cellular machinery guiding this process may have originated, but they emphatically said it does not buttress the case for intelligent design, a controversial notion that posits the existence of a creator responsible for complexity in nature.”
## Our mistake is to look at behavior and thus evolution through the prism of Time because this compels us to find The Prime Mover. And whether it is the God of Genesis or the God of Randomness, these are both Deities in their own way requiring the exact same leap of faith and this then precludes objective inquiry on what is happening right before us. It is a mistake to think in terms of a Creator (even though I am very comfortable with the notion of a Divine Intelligence) because this runs the evidence through the filter of causation. For example, these researchers uncovered the nature of this protein mechanism not by searching for its cause: in that case they would have settled for a gene theory, but by coming to understand how energy worked in the immediate moment. This is the same way physicists studied the atom, electron, photon, and so on. Science didn’t ask: What is the cause of electricity? In order to understand the nature of electricity they simply studied it in terms of the immediate moment and this manner of inquiry is so powerful that it then led science to understand the possibility of a Big Bang. So the irony is that only an immediate-moment analysis can apprehend the nature, and only apprehending the nature can allow us to offer educated guesses about causation. Likewise we shouldn’t interpret animal behavior through the prism of Time because then we will need to divine the source of their behavior via the notion of a Creator of some type.
In my view a better way to state the paradigm is: the DESIGN is in the INTELLIGENCE. For example, the “intelligence” inherent in electromagnetism is that it has a variable state of conductivity and this has gone on to evolve into the operating system of all computers. It doesn’t matter who invented the computer, because by virtue of electromagnetism being semi-conductive, the invention of the computer, and therefore even the internet of interconnected computers, is a foregone conclusion. It doesn’t matter who invented it, someone would have. The Hero will always remain faceless in our minds because of this certainty. Likewise, since emotion captures environmental energies as system inputs, and then it serves as a synchronizing medium for self-organization according to the variable conductivity of emotion, (once an organism acquires unresolved emotion it requires another individual to trigger and resolve it) sociability is as inevitable in the evolution of biological systems as the internet was in the evolution of the computer. ##
“Chakrabarti said that one of the aims of modern evolutionary theory is to identify principles of self-organization that can accelerate the generation of complex biological structures. "Such principles are fully consistent with the principles of natural selection. Biological change is always driven by random mutation and selection, but at certain pivotal junctures in evolutionary history, such random processes can create structures capable of steering subsequent evolution toward greater sophistication and complexity."
## All these recent breakthroughs (epigenetics, emergence theory and this protein-energy-transfer system as an example of PCT) that are now seen as “extending Darwin’s theory” (which I suppose they do if evolution isn’t seen as a gene driven theory in service to the God of Randomness), is for me not leading it down toward a deeper understanding but in the final analysis will be seen as slowly taking it apart bit by bit. ##
“In this paper, we present what is ostensibly the first quantitative experimental evidence, since Wallace's original proposal, that nature employs evolutionary control strategies to maximize the fitness of biological networks," Chakrabarti said. "Control theory offers a direct explanation for an otherwise perplexing observation and indicates that evolution is operating according to principles that every engineer knows.”
“The researchers are continuing their analysis, looking for parallel situations in other biological systems.”
## I’m proposing that what we are looking for, the fundamental mechanism underlying all other mechanisms whether physiological or psychological, is visible in the behavior of animals as an expression of energy. In other words, animals evolve as a network, their genes subscribing to its universal energetic logic, not the other way around. ##