SYSTEMOLOGY

Contents:

A system -
  1. a set of 2 or more interrelated entities, of which no subset is unrelated to any other subsets.
  2. a network of many variables in casual relationships to one another.
Systemology- the study of systems.

Types of systems:

  1. Naturfacts - trees,rocks,dirt,animals,etc.
  2. Artifacts - the things that people create.
  3. Mentafacts - ideas, emotions, symbols, etc.
In general: Naturfacts + Mentafacts -> Artifacts

Realms of reality:

  1. The world of the tiny & the quick- quantum world.
  2. The world of the huge & the whizzing- the cosmos.
  3. The world of me & it- see-&-touch world.
  4. The world of our interpretation- social sciences & arts.
  5. The world of the spirit- inner & personal world.
Basic Typology of Systems
  1. Gestalt structure or abstract systems.
    1. Programs.
      1. A pgm is a set of rules that control the system itself.
      2. Functions of programs:
        1. Descriptive - all possible sets of behaviors of the system.
        2. Normative- what behaviors the system can do or not do.
        3. Instructional- guides the system in choosing the correct behavior for a given environment.
      3. All systems have programs
      4. A healthy program is a program that is balanced.
      5. Systems that go against their pgm don't function well. They must change the pgm to fit them or change themselves.
    2. Communication.
      1. A msg contains information when it removes uncertainty in some way.
      2. Types of information:
        1. Energy
        2. Force
        3. Written/spoken language
        4. Gestures
        5. Chemicals
        6. Fields
      3. The process of communication- The sender uses a set of signs to construct a msg. A coding and transmitting device is then used to transmit the signal through a channel which may or may not contain noise. The signal is then received by a decoding & receiving device which is then decoded back into a msg that the receiver can understand.
      4. Noise- something that interferes with the sent msg & changes to a certain degree when it reaches the receiver.
        1. Syntactical noise- where the arrangement of the symbols is changed. Technical in nature.
        2. Semantic noise- when the sender's and receiver's sets of signs are dissimilar.
        3. Pragmatic noise- when the receiver's behavior to the msg doesn't match the sender's idea about how the receiver is supposed to behave. For example, the sender thinks the receiver should act happy to the received msg, but instead acts unhappy.
  2. Interacting natural dynamic systems (INDS).
    1. These are systems where components interact with one another in a population.
    2. Types of INDSs:
      1. Newtonian systems- matter.
      2. Chemical systems.
      3. Quantum mechanics.
      4. Einsteinien systems.
      5. Biological systems.
      6. Psycho-social systems.
    3. The components move from a high pressure environment to a lower pressure environment.
  3. Simple periodic dynamic systems.
    1. This is where the INDS show cycles or repetitive behavior.
    2. These systems are sometimes used for timekeeping purposes.
    3. Mode locking- a cycle of one system locks into another one where both are now in synchronous behavior.
    4. If two systems are interacting with one another & both of their "clocks" are not in conflict with one another then both systems will function well.
    5. Period 3 rule- In any 1-D system, if a regular cycle of period 3 ever appears, then the same system will also display regular cycles of every other length, as well as completely chaotic cycles. (James York, Chaos theory).
  4. Processing systems (PS).
    1. A PS takes an input processes it and converts it into an output.
    2. Toxic input- input that can't be processed by a particular system. Each PS has a certain set of inputs it can process, all other inputs are toxic.
    3. Once an input has been totally processed it is unproductive to reprocess it by the same system. Reprocessing can sometimes lead to the death of the system if not at least wasting the system's energy and time on reprocessing the input.
    4. Kinds of processes:
      1. Synthesis and catabolism.
      2. Form or shape changing.
  5. Cybernetic systems.
    1. These are systems that are goal oriented.
    2. Components.
      1. Feed forward- a sequence of responses the system can make at some future time.
      2. Feed back- data about the system's past or present.
      3. Goal - what the system is aiming at.
      4. Output- the system's behavior to achieve the goal.
      5. Disturbances- anything that will make the system deviate from its goal.
    3. To guarantee that the system is efficient at attaining its goal the following conditions must be filled.
      1. The system must have info about the disturbances.
      2. There must be enough control measures.
      3. There must be a criterion on which to base the choice of a control procedure by comparing the system's predicted behavior with the goal.
    4. Types of cybernetic systems.
      1. Cause-controlled systems- the state of the system is defined directly by the environment.
        1. The impact of the disturbance is counteracted before it is able to affect the magnitudes the system wants to control.
        2. In order to be able to have effective control, all possible disturbances influencing the process must be known.
        3. For a caused-controlled system to function properly it is essential for the system to know exactly how a certain disturbance affects itself, so that the system can adjust the cause-control correctly.
      2. Error-controlled systems- the reaction of the system is defined by the difference between the actual and the desired value of the magnitudes which are to be controlled.
        1. They start functioning only when there is a difference between desired and actual values.
        2. It makes no difference to their functioning whether the disturbance is known or unknown, expected or unexpected (as long as it remains within the range of error-control). In order to determine the appropriate control action, the system itself is used as a model.
        3. They may be unstable.
        4. Independently of their state, they will still attempt to bring the actual value into agreement with the desired value.
    5. Equilibrium state possible- the state the system attains or settles into. A state is the set of relevant properties which the system has at a particular time.
    6. Equifinality- a system that can reach the same final state from different initial states and in different ways.
    7. Ultrastable- a system that cannot return to its initial state because conditions in its environment have changed, so it finds another stable state different from the initial one.
    8. Competition is possible with these systems. Competition can happen when there is a scarcity of goals, and two or more systems want the same goal.
    9. When a cybernetic system is controlling another system the controller must have fundamental tempo many times faster than the controllee, since it has to anticipate every eventuality & possibility & it has to also have reserve time for "thinking".
    10. Can communicate with other cybernetic systems. The communication process:
      1. System A sends a msg to system B.
      2. B processes the msg & repeats the msg back to A.
      3. A compares the msg it received from B, to the msg it sent to B.
        1. If they're essentially the same, then A sends a 'right' or 'OK' msg to B & B can then proceed using the msg. A can proceed as well.
        2. If they're essentially not the same, then A sends a 'not OK' msg. B can either ask for the msg again, or wait for A's reply which can be an 'ignore the msg' or the same msg again. (A could also send the msg again, instead of sending the 'not OK' msg).
  6. Autopoiesis systems (self-maintaining systems).
    1. An autopoiesis system is a system which composes, creates, invents itself.
    2. Knows it is separate from the environment.
    3. Characteristics.
      1. There is a system consisting of a large number of microscopic elements. The system initially is in a relatively undifferentiated state.
      2. There are self-amplifying fluctuations in (ie, deviations from) the undifferentiated state.
      3. Some limitatiion of resources forces competition among fluctuations and selection of the fittest (ie the most vigorously growing) at the expense of others.
      4. Fluctuations cooperate. The presence of a fluctuation can enhance the fitness of some of the others, in spite of the overall competition for resources in the field.
      5. Whole systems of cooperatively interacting fluctuations emerge as ordered, differentiated states, or ordered modes- the order often extending over a wide area.
    4. Steps of self-maintaining systems:
      1. Searching and screening for available information.
      2. Analyzing, breaking down the information.
      3. Manipulating that information into new synthesis.
      4. Using this new recombined info for the system’s benefit.
      5. The synthesis actual affect on the system is fedback to the system.
    5. Bifurcation point- a point in the systems state that because it is open that the fluctuations may become so powerful that it cannot withstand the fluctuation. A system at this point has two options. Either it will be destroyed by the fluctuation and disintegrate into randomness or it will suddenly leap to an entirely new level of organization that will dissipate the influx of info responsible for the disabling fluctuation.
    6. Le Chatelier's principle: A system will modify itself so as to resist any changes that another system are trying to bring about.
    7. The ultimate goal is survival.
    8. Living systems..
      1. are highly organized.
      2. are homeostatic, which simply means "staying the same".
      3. take energy from the environment & change it from one form to another.
      4. respond to stimuli.
      5. can adapt.
(Type B to F Systems go from low to high in complexity. Type A systems are in a separate classification by themselves.)

General principles and terms:

  1. Environment- what isn't a subset of the system.
  2. Types of environments:
    1. Least complex- placid randomized environment. The favorable & harmful influences on the system is divided relatively uniformly, unchangeable, & unchanging in their distribution.
    2. More complex- placid clustered environment. Some of the favorable & harmful influences are in clusters. The clusters are stable.
    3. 'Disturbed reactive environment.'- a type 2 environment, in which there is more than one system of the same kind interacting.
    4. 'Turbulent fields'- a type 3 environment where the clusters in the environment are always changing.
  3. Open system- where a system interacts with its environment. Most systems are open.
  4. Closed system- where a system does not interact with the environment.
  5. State- the set of relevant properties which that system has at a certain time.
  6. Types of states:
    1. Transient state- a state that changes in time. Most systems change over time.
    2. Steady state- a state that is constant in time.
  7. Entropy- the measure of disorder.
  8. Syntropy- the process of a system to go from a lower level of organization to a higher-level.
  9. The functions of entropy.
    1. No entropy (complete order)- no change in the system.
    2. All entropy- constant change in the system.
    3. If a little bit of entropy, but not greater than the measure of order, then gradual change will happen.
  10. Death- when a system ceases to function & ceases to be recognized. This latter definition may be sufficient by itself to define death.
  11. Law of inertia for systems: A system in motion will stay in motion unless acted upon by a counter-motion force.
  12. Higher level systems can have lower level subsystems.
  13. Combining systems:
    1. Synergism- the action of 2 or more systems to achieve an effect of which each is individually incapable.
    2. Asynergism- 2 or more independent functioning systems combining to form a new system which is incapable of functioning.
    3. Synthesism- 2 or more independent systems combining to form another different system.
  14. The steps of evolution:
    1. A system is created that the creator thinks will hopefully survive in its environment.
    2. If it doesn't survive the creator creates another similar system with a mutation or a modification hoping that the system will survive. If it does survive, no modification is done & the system continues to be created.
  15. A new evolution model.
    1. Selection of the fittest.
    2. Symbiosis.
    3. Directed mutation.
    4. Saltattonism.
    5. Self-organization.
  16. Symbiosis- 2 systems in close proximity to one another.
    1. Phoresis- casual contact, neither is affected.
    2. Commensalism- neither is harmed.
    3. Mutualism- both are benefited.
    4. Parasitism- one is harmed, the other benefits.
  17. A newly created system has the potential for displaying destructive behavior & constructive behavior.
  18. Critical or key variables- variables that interact mutually with a large number of other variables in the system. Altering them will exert a major influence on the status of the entire system.
  19. Indicator variables those variables that depend on many other variables in the system but that themselves exert very little influence on the system.
  20. Kauffmans Law: Above a certain point, increasing the richness of connections between agents in a network freezes adaption.
  21. Cause & effect are not closely related in time & space.
  22. Small changes can produce big results- but the areas of highest leverage are often the least obvious.
Complexity Theory:
  1. Chaos happens when at a given point a system has a set of possible behaviors which out of one is selected depending on conditions the point represents. This is what makes the system nonlinear. Each behavior has its own unique conditions that activate that behavior.
  2. Attractor- a state that eventually complex systems show.
    1. Point attractor- when a system uses up its energy to sustain itself it eventually comes to this attractor, and ceases. The system cannot escape this attractor, unless it gains energy.
    2. Limit cycle attractors- a periodic attractor.
    3. Torus attractor- 2 or more limit cycle attractors combined together.
      1. Rational torus- where the torus attractor repeats the same values.
      2. Irrational torus- values are not repeated exactly.
    4. Strange attractor- a very broken up, seemingly unpredictable toridial attractor. (most complex)
  3. The more complex the system, the further away cause & effect usually are from each other in both space & time.
  4. Lotfi Zadeh’s Law of Incompatibility: As complexity rises, precise statements lose meaning & meaningful statements lose precision.
  5. Sensitive dependence on initial conditions principle: Tiny differences in input could quickly, become overwhelming differences in output. Also known as the Butterfly Effect.
  6. Logical depth- the time it takes for a minimal algorithm to run. The more complex a system is the more time it takes to run the algorithm, ie its logical depth is deeper.
  7. If a linear process is slightly disturbed it goes into another different state & stays there, but a nonlinear process tends to go back to its previous state.
  8. Simple systems give rise to complex behavior.
  9. Complex systems give rise to simple behavior.
  10. The main surprise-generating mechanisms.
    1. Paradoxes.
    2. Instability- large effects from small changes.
    3. Uncomputability- behavior transcends rules.
    4. Connectivity- behavior cannot be decomposed into parts.
    5. Emergence- self-organizing patterns.
  11. The Kolmogorov complexity of a system- the least number of bits of info required to describe exhaustively the system.
  12. Wolfram's classes of complexity.
    1. Pattern disappears with time or becomes a fixed, static, homogeneous state.
    2. Pattern evolves to a fixed finite size, forming structures that repeat indefinitely.
    3. Chaotic states.
    4. Complex patterns grow & contract irregularly.
Primitives or unities of systems:
  1. Matter- electrons, quarks.
  2. Written language- letters, punctuation.
  3. Spoken language- morphemes.
  4. Mind- agents (Marvin Minsky), cognitions, emotions, values, instincts, reflexes.
Building systems:
  1. Casual flow diagramming.
    1. Steps.
      1. Identify major dynamic factors.
      2. Identify cause-&-effect relationships.
      3. Characterize the relationships as direct or inverse.
      4. Diagram the relationships.
      5. Analyze the behavior of the relationships as integrated systems.
    2. If all of the linkages are direct relationships, the feedback loop is inherently unstable.
    3. If there is an even number of inverse linkages, the loop is unstable.
  2. Ten commandments of creating a system:
    1. Preserve variety.
    2. Do not “open” regulatory loops.
    3. Look for the pts of amplification.
    4. Reestablish equilibriums through decentralization.
    5. Know how to maintain constraints.
    6. Differentiate to integrate better.
    7. To evolve, allow aggression.
    8. Prefer objectives to detailed programming.
    9. Know how to use operating energy.
    10. Respect response time.
  3. Tips on studying & building systems:
    1. When discovering a rule/law in one particular discipline ask yourself can this law be applied to other disciplines?
    2. When introducing a system to the environment do it slowly, so other systems can adjust to it.
    3. Always keep in mind the Butterfly Effect when creating a complex system.
    4. If possible, simulate or model the system on a computer.
    5. When studying a system always try to be honest. Objectivity is OK, but it is harder to be objective than honest.
    6. When replacing an old system for a new one be sure that the replacer system is better than the replacee.
  4. Principles of good design.
    1. Visibility- the user can tell what the state of the device is.
    2. A good conceptual model. The user’s conceptual mode should be the same as the designer’s.
    3. Good mappings. There should be a clear relationship between actions & results, & between the controls & their effects.
    4. Feedback- the user should receive full and continuous feedback about the results of actions.
    5. Design to minimize the causes of errors.
    6. Make it possible to reverse actions or make it harder to do what cannot be reversed.
    7. Make it easier to discover the errors that occur, & make them easier to correct.
    8. Change the attitude toward errors. Think of an object’s user as attempting to do a task, getting there by imperfect approximations.
    9. Put the requirement & knowledge in the world. Don’t require all the knowledge to be in the head. Yet do allow for more efficient operation when the user has learned the operations, has gotten the knowledge in the head.
    10. Use the power of natural & artificial constraints. Use forcing functions.
    11. Simplify the structure of tasks.
  5. Generic recipe for distributed control.
    1. Do simple things 1st.
    2. Learn to do them flawlessly.
    3. Add new layers of activity over the results of the simple tasks.
    4. Don’t change the simple things.
    5. Make new layers work as flawlessly as the simple.
    6. Repeat, ad infinitum.
  6. Nine laws of God.
    1. Distribute being.
    2. Control from the bottom up.
    3. Cultivate increasing return- positive feedback.
    4. Grow by chunking- the only way to make a complex system that works is to begin with a simple system that works.
    5. Maximize the fringes- a diverse heterogeneous entity can adapt to the world in a thousand daily minirevolutions, staying in a state of permanent, but never fatal, churning.
    6. Honor your errors.
    7. Pursue no optima; have multiple goals.
    8. Seek persistent disequilibrium.
    9. Change changes itself.
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