Systems theory

Systems theory

Introduction


Life has existed on our planet for millions of years and has slowly become more complex over time through a process called evolution, which in simple terms is called 'trial and error'. Life has been and still is in a constant battle with Entropy, which you might know as death or chaos - Everything that is built will eventually crumble, especially if its not being looked after.


The major issue for life was the requirement of energy to reduce entropy, any action taken has a cost and seeing as every lifeform has a finite amount of energy we run into a problem - This is where information comes in; seeking out patterns in order to make growing in complexity and reducing entropy more effective. But in order to retrieve information about the direct environment a certain type of algorithm had to be produced - You can compare this process to your phone, a more efficient way to stay in contact with other individuals in comparison to sending letters - This is where the system comes in


What is a system? 


Hold onto your horses as things are going to get freaky, a system is a sentient entity that adapts to its environment - A system can be organic like you and me, organizational like a business, solar like our own galaxy, a religion or a thought pattern. 


A system has three primary components; structure, metabolism & information - Structure can be your bones and muscles, a set of rules within a company or the walls of a building - Metabolism comprises primarily of the moving parts, like the human beings of a business, the metabolic processes in our body or the movement of planets in line with the sun - Information is anything that is measured, is used for patterns or supplies energy.


What is the primary intent of a system?


First and foremost is to reduce entropy (fight death), and it does this by surviving and procreating. It's important to understand that surviving has a higher priority than procreating, we all like sex but when there is an imminent threat our libido drops to zero.


It reduces entropy by gathering raw data from its environment and producing information which in term can be used for pattern recognition which is often termed knowledge and/or wisdom. 


How does a system formulate its own actions?


It does this by calculating probabilities through an algorithm which we call the Bayesian inference (more on that later), it predicts the likelihood of imminent death and potential gain. The lesser the chance of imminent death the greater the expenditure on processes with a procreating nature - However if the chance of death increases the behaviour shifts towards that of preserving rather than creating.



How does the systems theory tie in with training


As stated before, all the actions that we take are to reduce uncertainty (entropy) the same goes for any type of training - Willingly exposing yourself to chaos will make you more adept at dealing with a similar source in the future, and thus reducing the chance of death.

We've also formulated that a systemical approach to reducing uncertainty is far superior in terms of computational power (setting probabilities), hence why I HIGHLY recommend systemizing your training - Not only will give this approach a superior benefit to you the organism, it also requires less effort to execute and increases evolution and adaptability over time

How can I use these systems


The keyword is experience, experiencing a benefit through anecdotal evidence - Which is why I won't divulge too much information and ask you to read the preceeding blog posts