#problem blog

[tallpplproblems]

Tall People Problems #1

Having to duck when getting on/off a bus

[problemblogproblems]

When tumblr is ruining your life but you can't leave it

[problemblogproblems]

When you have so many feels you can't feel anything anymore

[problemblogproblems]

When "finding the d" isn't so fun, because it's on your report card

[theproblemblog-blog]

Problem 0: Defining a Problem (part two)

Before we can go about ranking, sorting, discussing or fussing about problems, we need to get at what makes a problem a problem. I'm taking a 4 variable system for sorting these bad-boys, which define a problem by how it is solved and how it is prolonged. This is admittedly the least scientific solution to the problem of defining problems, and that's just fine. If we solve a problem, then we solve a problem, no questions asked. My variables for problem description are as follows:

Effort. Problems take effort to solve and they can become big problems if the effort required to solve them is too costly. 'Effort' itself is a big term encompassing things like: time spent, force exerted, and resources used. We can either have a low effort problem (which means it can be resolved without seriously impacting the solvers time, labor, or resources at hand), a high effort problem, and two spectrum of what I'm going to introduce here as 'impossibility.' What do I mean by impossibility? We're going to have to face at some point that some problems can't be solved even if we want to solve them, and that is because they have a property of impossibility. When we speak of impossibility of effort, we mean that either something is so monumentally effort-based that there just aren't enough resources, time or energy to solve the problem, or that the problem requires such a small effort that it is destroyed somehow in the process of solving just because effort is present, say we would like to transport a very beautiful cobweb to a museum, it just wouldn't be possible to keep that cobweb intact in the process. That's impossibility. 

Ahem. Intermediary Nature. Tasks can be so simple that it's literally one step to complete them, they can also be a series of trips, plannings, meetings, conceptualizations, advancements and so forth before the problem is resolved. This is the Intermediary Nature of a problem: how many points and events between problem formation and resolution need to pass before the end is met. The impossibility of Intermediary Nature's two extremes are in the un-satisfiable Intermediate step, the low end of impossibility, and what we colloquially call the Catch 22 at the high end of the spectrum. 

Finiteness. This one is quite a lot simpler than the other two. Either a problem has an end step or it does not. Finiteness measures a binary between accomplish-able(at least theoretically) and infinite problems. There is an impossiblity to Finitenes, though only one version of it meets our theme of high and low impossiblity stages, the low being a situation where the finite ending to a solution has already occurred, rending the problem theoretically solved but rationally unsolvable, and the other being a systemic failure, where we are given a sound resolution point, but the systems we are using to solve the problem are in conflict with the resolution, as sometimes happens in mathematical models or when a scientific theorem is found to be incorrect (or an anomalous event occurs).

And last: Propagation. There are undoubtedly some solutions to problems that we refuse to carry out because we are aware that the solution will cause one or more other problems to come into existence, at which point we can say that the problem will 'propagate' more problems if it is allowed to meet it's natural course of being solved. The impossibility for this term is something like a logic loop, if the problem recreates itself when it is solved, then we have a high propagation impossibility, and at the low end we have what would be called the bridge burning effect. That is to say that solving the problem would cause an event that causes it's resolution useless. The impossibility of these two lays more in the impossibility of solving  problem 'forever' than being actually impossible to arrive at, as the other three tend to be. 

So there we have it, E I F P, the four terms we'll use to try and root out every possible type of problem and hopefully gain some insight to their workings. I'll denote the levels of each variable by their capitalization, Eifp being a problem that's only particularly high variable based problem is the amount of effort that it needs to resolve. 

Let's try it out with the baseline for all problems, eifp.

The low end of the problem scale we're devising here is the Ob-Problem, with Ob standing for Obstacle. These are what we would consider rudimentary problems such as a basic math problem. This is also the problem encountered in unconscious effort based process, such as the motor actions required to get a glass of water when thirsty. There problems will mostly be ignored by our blogging ritual, but they provide an important framework for how problems inherently work and are solved. It has an inherently simple process, which is helpful as we add more and more to it as our problems grow more complex, and it also shows us two important points in a problem, the appearance and resolution.

Characteristics and Procedure of a Ob-Problem:

1. A process of need, desire, or automatic process is interrupted by an obstacle to the end of the process. (Appearance of Problem)

2. Effort is expended in order to resolve the obstacle's interference in less than a significantly costly manner. (Resolution of Problem)

All four of our variables are at their lowest levels during this problem, making it seem like not much of a problem at all, but this is probably also the most common problem, practically legion in number and occurrence compared to our more dastardly subjects. Next segment we will categorize and make a grand list of possible problems, and go about reducing and finding redundancy within their patterns.

[theproblemblog-blog]

Problem 0: Defining a Problem (part one)

Problems are not a well defined subject, nor is 'problem' a well defined word. The lack of clarity in the meaning of problems is, well, a problem. It's especially a problem for us, the problem solvers to be, because if we want to solve any problems we need to know what a problem really is. So, before any problems get examined, unraveled, dissected, discussed or decided, we'll have to figure out what a problem is, what the problems with the definitions problem holds, and what we can do to fix the problem of defining a problem.

Wikipedia provides, perhaps, the best definition. It does so by combining several meanings of problems into one. That is to say the difference between a mathematical problem and a lemma based problem (such as a di-lemma).

"A problem is an obstacle, impediment, difficulty or challenge, or any situation that invites resolution; the resolution of which is recognized as a solution or contribution toward a known purpose or goal. A problem implies a desired outcome coupled with an apparent deficiency, doubt or inconsistency that prevents the outcome from taking place."

Which is great; it covers everything that a problem should be, and that's essentially anything that is un-resolved and requires some effort based input to conclude. We can put this definition to the test and rule out some things that seem like problems but which are not, in fact, 'problems.'

One example of something that is not a problem would be something like a lemma which solves itself, or a win-only scenario. Consider the fork in the road dilemma: you are confronted with a fork in the road which is unmarked, your dilemma is that you have a certain presumed destination and that you need to reach that destination by road. The only time this dilemma becomes a 'problem' is when only one of those roads continues to your destination. If both roads will take you to your destination then you have arrived at a point of confusion, but not a problem (though we can argue that the lack of clear sign posting on this road is a problem if the 'problem to be solved' at hand is the confusion created by the lack of clear guidance, which can only be resolved by an effort of someone or some other force to reach a conclusion).

The existence of a win-only scenario also makes the loss-only scenario a consideration we need to investigate. A loss-only scenario is a problem because of what we can call the 'resolution'. In the win-only situation we have a desired resolution that we inevitably meet, nullifying the problem no matter which choice we make, but in a loss-only scenario we are denied the resolution no matter which choice we make. This is a more philosophical problem at first glance, but we can also think of a few real-world loss only scenarios, especially in math, the Twin Prime problem for example: we can infinitely seek the twin primes and are denied resolution, or we can give up seeking the solution and be denied resolution. Though, we may have difficulty defining what makes a problem completely loss-only and what makes a problem loss-only, but only in isolation. We can deal with this later, though.

There is one last problem that you might call a non-problems depending on your viewpoint. That would be a systemically controlled non-problem. An example of this would be breathing. Breathing is a solution to a very specific oxygen intake problem that living creatures have. However, not a lot of people have trouble breathing, as it is an unconscious process. There was also a problem at some point in evolution where some organism could benefit from oxygen's intake, but had no systems to accomplish this. In a larger sense this is a problem (a difficult task that needs to be solved via some effort), but it's also a systemically controlled non-problem, that system being the evolutionary system. This really begs the big question that we need to resolve here and now: does a problem have to be a conscious act? We can see that there are times when no one is actively aware of the problem, yet it is a problem. On the other hand, these problems are typically solved automatically by a system (though that is changing with modern technology), so are they even worth considering a problem? Tough questions, but for the sake of this discussion we will consider any problem that is regularly solved by a systemic force to be a non-problem.

This difference in problem and non-problem is acceptable for our use, however, we also need to let the different problems within the grand scope of problem related scenarios come apart and be defined individually in order to advance our purpose of exactly defining a problem. This is to separate the problems that need to solved, the problems that want to be solved, the problems that cannot be solved, and the problems that are solved. We also want to examine the process behind these problems, or to be put more simply, what it is that makes these problems acceptably within the definitions of a problem; which is exactly what we will do in the next installment.