Is the P=NP Problem an NP Problem?

What I’m going to say is going to be unpopular, but I cannot reconcile my own well-being without giving you an answer to this problem from my perspective.

My only reason for reluctantly writing this, knowing what kind of reaction I could receive is, because I abhor that some of the best minds on our planet are occupying themselves with this problem. It pains me to no end to see humanity squandering its power for a problem that, as it is currently framed, is unanswerable. It goes further than this though. There will come a time when questions such as this one will be cast upon the junk heap of humanity’s growth throughout history. It will take its rightful place along such ideas as phrenology.

Here’s why I say this:

The problem is firmly and completely embedded in Functional Reductionism. I say this, because the problem’s framing requires us to peel away the contextual embedding of the problems which it is supposed to clarify.

This is just one of its problems. Here’s another:

Since the data for this problem (and those like it) are themselves algorithms, they are compelled to be functionally reduced versions of mind problem solving (varying types of heuristics and decision problems) which reduces the problem’s causal domain and its universe of discourse even further. How can a specification based upon functionally reduced data be again used as data for the problem’s solution in the first place?

That means that this problem has no independent existence nor causal efficacy. Everywhere I have looked at this problem, the definitions of NP-Hard and NP-Complete do not lead to proving anything useful. We cannot ‘generalise’ the mind by reducing it to some metric of complexity. Complexity is also not how the universe works as Occam’s Razor[1] shows.

I am prepared to defend my position should someone have the metal to test me on this. Another thing: I wish I could have left this alone, but we all need to wake up to this nonsense.

[1] http://bit.ly/2GHbRkW How Occam's Razor Works

[Quora]
http://bit.ly/2EuRdP3

Knowledge Representation - Holographic Heart Torus

Holographic Heart Torus by Ryan Cameron on YouTube

Knowledge Representation - Fractal Torus 1

Fractal Torus 1 by Ryan Cameron on YouTube

Is Real World Knowledge More Valuable Than Fictional Knowledge?

No.

Here an excerpt from a short summary of a paper I am writing that provides some context to answer this question:

What Knowledge is not:

Knowledge is not very well understood so I'll briefly point out some of the reasons why we've been unable to precisely define what knowledge is thus far. Humanity has made numerous attempts at defining knowledge. Plato taught that justified truth and belief are required for something to be considered knowledge.

Throughout the history of the theory of knowledge (epistemology), others have done their best to add to Plato's work or create new or more comprehensive definitions in their attempts to 'contain' the meaning of meaning (knowledge). All of these efforts have failed for one reason or another.

Using truth value and 'justification’ as a basis for knowledge or introducing broader definitions or finer classifications can only fail.

I will now provide a small set of examples of why this is so.

Truth value is only a value that knowledge may attend.

Knowledge can be true or false, justified or unjustified, because

knowledge is the meaning of meaning

What about false or fictitious knowledge? [Here’s the reason why I say no.]

Their perfectly valid structure and dynamics are ignored by classifying them as something else than what they are. Differences in culture or language even make no difference, because the objects being referred to have meaning that transcends language barriers.

Another problem is that knowledge is often thought to be primarily semantics or even ontology based. Both of these cannot be true for many reasons. In the first case (semantics):

There already exists knowledge structure and dynamics for objects we cannot or will not yet know.

The same is true for objects to which meaning has not yet been assigned, such as ideas, connections and perspectives that we're not yet aware of or have forgotten. Their meaning is never clear until we've become aware of or remember them.

In the second case (ontology): collations that are fed ontological framing are necessarily bound to memory, initial conditions of some kind and/or association in terms of space, time, order, context, relation,... We build whole catalogues, dictionaries and theories about them: Triads, diads, quints, ontology charts, neural networks, semiotics and even the current research in linguistics are examples.

Even if an ontology or set of them attempts to represent intrinsic meaning, it can only do so in a descriptive ‘extrinsic’ way. An ontology, no matter how sophisticated, is incapable of generating the purpose of even its own inception, not to mention the purpose of the objects to which it corresponds.

The knowledge is not coming from the data itself, it is always coming from the observer of the data, even if that observer is an algorithm.

Therefore ontology-based semantic analysis can only produce the artefacts of knowledge, such as search results, association to other objects, 'knowledge graphs' like Cayley,…

Real knowledge precedes, transcends and includes our conceptions, cognitive processes, perception, communication, reasoning and is more than simply related to our capacity of acknowledgement.

In fact knowledge cannot even be completely systematised; it can only be interacted with using ever increasing precision.

[For those interested, my summary is found at: A Precise Definition of Knowledge - Knowledge Representation as a Means to Define the Meaning of Meaning Precisely: http://bit.ly/2pA8Y8Y

What About Tacit Knowledge?

A knowledge representation system is required. I’m building one right now. Mathesis Universalis.

There are other tools which are useful, such as TheBrain Mind Mapping Software, Brainstorming, GTD and Knowledgebase Software

Products and technologies like TheBrain, knowledge graphs, taxonomies, and thesauri can only manage references to and types of knowledge (ontologies).

A true knowledge representation would contain vector components which describe the answers to “Why?” and “How does one know?” or “When is ‘enough’, enough?” (epistemology).

It is only through additional epistemological representation that tacit knowledge can be stored and referenced.

A Holon's Topology, Morphology, and Dynamics (2a)

A Holon's Topology, Morphology, and Dynamics (2a)

This is the second video of a large series and the very first video in a mini-series about holons. In this series I will be building the vocabulary of holons which in turn will be used in my knowledge representations.
The video following this one will go into greater detail describing what you see here and will be adding more to the vocabulary.

This is the second video of a large series and the very first video in a mini-series about holons. In this series I will be building the vocabulary of holons which in turn will be used in my knowledge representations.

#Knowledge #Wisdom #Understanding #Insight #Learning #MathesisUniversalis #ScientiaUniversalis #Holons   #BigData