FORMAL / LOGICAL SYSTEMSENTICS Entics, the science of entities, otherwise known as the entic science, is a discipline that has a long history, but is rarely named as such. It is viciously divided between an empirical approach (biology, physics, etc.) and metaphysical philosophy (ontology, how things exist). I. Entics may be described initially in terms of an item, and the datum in which the item is understood.Depending on the manner in which entities are interpreted, the datum may take the form of mathematical dimensions, a context of interaction (such as intelligent networks), or a logical relationship such as a philosophical system or linguistic pattern. II. Ideally, entities (items) have some kind of significance in terms of the formal context in which the item is being interpreted. A common result is to find that the item falls into the following classifications: 1: Trivial (not affecting the context at all). 2: Un-exceptional (not affecting the context meaningfully). 3: Typical (affecting the context in a normal way). Additionally, some items may in some cases be (0:) completely meaningless (be careful with this by using absolute criteria), but otherwise if they don't fit into the above, they fall into the following more advanced categories: 4. Functional (following a predictable pattern). 5. Organized (having a particular effect). 6. Exceptional (following a characteristic pattern). 7. Unique (having a highly notable effect or pattern). 8. Game-changing (changing the way the datum behaves)As can be seen, this initial type of analysis results in ranking items in terms of their uniqueness, with the assumption that unique internal logic defines unique external logic. III. Next, at a more advanced level we have relations of multiple objects (symbols) or items (entities), and we wish to find common significance amongst them. This can be done through the following properties: 1. Existence (Yes / No). 2. Commonality (Degree / Characterization) 3. Oppositeness (Opposition / Exclusion) 4. Modal Similarities (Opposed but similar? Basically similar or basically different?) 5. Unique Attributes (Common and different classifications) Readers may note the similarity to principles from syllogisms, such as existence and exclusion. This process serves to classify in exactly which ways, vis. the earlier categories, these items, objects or entities express exterior attributes.IV. An important tool in entics is the concept of 'digging' which is an additional extension of analysis which asks us to get the most out of any one concept. Effectively, the only limitation on digging is normativity which defines that a previous object is already significant. Thus, a first rule of entics is that items tend to be significant. This is because the only possibility of finding significance for an object is finding some way in which it has significant for other objects which are already significant. Thus, an object has to be doubly-significant to have special significance. Simply relating with one significant object is not enough, and relating with two objects may require some form of logic. A second rule is that items express interior logic through relevance, or else through experience .Thus, some of the broadest possible categories of relevance and experience might be helpful: Relevance Experience: 1. Appearance. 2. Influence. 3. Symbolism. 4. Scintillation. Experience: 1. Notion. 2. Representation. 3. Excitation. 4. Awareness. Thus we get the primary logic for internal entities through the following: {(Appearance & Influence & Symbolism & Scintillation) V (Notion & Representation & Excitation & Awareness)} Thus, relevance and experience are fundamentally based on causes (scintillations, etc.) and origins (notions, etc.). Thus, an entity may be explained generally as a causal origin.V. (The role of Quantificcation).In some cases a system exists exclusively through quantification, and it is quantification that expresses the existence of system. This is true for example, with simplified concepts of evolution or Moore's Law of Computing (that technology quadruples its complexity every six months, or something like that). In these cases, the entity (such as technology) represented by the system (such as technological growth) amounts to a power difference. Thus, the system amounts to a number such as 2, 3 or 4 which represents an exponent on a field of data. Most other differences expressed in these terms are variations within pre-existing data, such as can be accommodated by adding or subtracting large numbers from the equation's data set. For example, with anthropological data about someone's age, we might predict longer potential age the longer someone succeeds to survive. So, actual age can be approximated as an extended tail with a probability of (1 / sq root of n) + (1 / the average life expectancy in years) , where n is the number of years lived.BACK TO SYSTEMS |