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GitHub is where people build software. More than 56 million people use GitHub to discover, fork, and contribute to over million projects.� Question: is it possible to modify different DMatrix columns in parallel (via Rayon) without Mutex? 1. Find more good first issues >.� Open-source symbolic algebra library for C# and F#. One of the most powerful myboat110 boatplans parse latex csharp parsing integration calculus algebra jupyter math computer-algebra wiki nuget solver arbitrary-precision symbolic-manipulation equations differentiation inequality symbolic-math. Open-ended questions are a great way to get more information from the person answering your question. By their very nature, they beg for more details. And so, I�ve compiled an enormous list of open-ended questions that you can use to understand them better or just to ask. But first, let�s look at what open-ended questions are. Click here for this page en espanol. What are open-ended questions? To put it as simply as possible, open-ended questions are questions that require more than a short, fixed response. Open-ended questions try to avoid answers like �Yes.�, �No.�, �The Battle of Midway.�. Open ended questions are used for interviews, with the caveat that there are those with no right or wrong answers.� Open ended questions in surveys solicit additional information to be contributed by respondents. They are sometimes also called infinite response questions or unsaturated type questions. Generally, close-ended questions require respondents to answer in just one or two words. Reduce Errors. Open ended questions cut down on two types of response error; respondents are not likely to forget the answers they have to choose from if they are given the chance to respond freely, and open ended questions simply do not allow respondents to disregard reading the questions and just "fill in" the.

Open-ended natural selection of interacting code-data-dual algorithms as a property analogous to Turing completeness. Work fast with our official CLI. Learn more. If nothing happens, download GitHub Desktop and try again. If nothing happens, download Xcode and try again. If nothing happens, download the GitHub extension for Visual Studio and try again.

GitHub repo has preview only. The intended view is only on GitHub Pages better with Javascript on. UPD : It is advised to start reading from Open-ended natural selection of interacting code-data-dual algorithms as a property analogous to Turing completeness article.

I seek advice or any other help available regarding creating a specific mathematical model. This approach implies indeterminism and postulates random and spontaneous nature of some events. It is also assumed that the universe had the first moment of existence with relatively simple structure.

The key idea of this research program is to create an artificial universe in which we can answer any questions like "why is the present is this way not another?

Moreover the model itself needs to have some justification to be a candidate for model of the our real universe. There are two main intuitions-constraints for this universe: 1 the start from the simple enough state the beginning of time , 2 the complexity capable of producing sentient beings after enormous simulation time of course comes from natural selection which postulates are provided by universe model rules.

The two intuitions give hope that the model to build would be simple and obvious in retrospect like postulates of natural selection are simple and obvious in retrospect they are obvious, but until Darwin formulated them it was really hard to assume them.

So there is a hope that it's feasible task. The model to build is a model of complexity generation. At later steps the complexity should be capable of intelligence and self-knowledge. Sadly I have not moved far to this goal. I'm still in the situation of "I feel like the answer the this grand question can be obtained this particular way".

The best tool I know that can historically explain why the particular structures exist is Darwin's evolution with natural selection. And the best tools to justify the model of reality are falsifiability and Occam's razor.

First states that the theory should work and be capable of predictions. The second states that among models similar in respect to falsifiability the simplest one should be chosen. If we are to go with natural selection as novelty generating mechanism then we should think that Lee Smolin's Cosmological natural selection CNS hypothesis is likely to be true. And that means that our observable universe could have had a very large number of universes-ancestors.

This means that it would be really hard to apply falsifiability to the model to build. In the best case when built sic!

In the worst case we only get the restriction that our universe is possible in the model. Luckily we also have an artificial life open-ended evolution a-life OEE restriction and Occam's razor. OEE means that at least in itself the model must show specific dynamics.

And we already can assume that the model should be as simple as possible and if the assumed simplicity is not enough then we should make it more complex. Though simplicity by itself cannot be a justification I have a hope that selecting the simplest workings from many working a-life OEE models could be a justification proof of the theorem that the selected workings should be in every a-life OEE would be even better.

And I mean a justification for basic rules that govern the dynamic of the model. By the way, this way we can justify a model obtained via any other research program. So if some "Theory of everything" appears we don't need to ask "why this particular theory?

Instead we should check for other simpler? Because of what? The research program uses the artificial life model with natural selection as a basis. This means taking inspiration in natural selection of biological life NS.

Also adding Occam's razor OR to the picture. In order to continue we need to precisely define what are individuals in the model and environment if needed and how the process of their replication and death takes place. There are some properties of the model we can assume and go with:. If we assume that complex laws are emergent from algorithms then what about quantum computers? It can be formulated as "Is bounded-error quantum polynomial time BQP class can be polynomially solved on machine with discrete ontology?

What is your opinion and thoughts about possible ways to get an answer whether problems that are solvable on quantum computer within polynomial time BQP can be solved withing polynomial time on hypothetical machine that has discrete ontology? The latter means that it doesn't use continuous manifolds and such. It only uses discrete entities and maybe rational numbers as in discrete probability theory? If we go with natural selection, use biological life as inspiration and go with assumptions above then we should answer the question: what is the inanimate matter?

For biological life the inanimate matter is only an environment. And if we have only individuals in the model then why the inanimate matter in our Universe is so stable? After all in the biological life there is always the threat of cancer that is an error in the reproduction algorithm. Why some elemental particles never ever "mutate"?

This requires explaining via model assumptions or correcting them. You can discuss the letter on GitHub or Reddit. This introduction actually contains everything important that is in this article.

So the rest text at best can add some details to the picture or answer some questions. At worst it can be outdated and no longer reflects my opinion. Presumably the environment will be other individuals, and there would be nothing but individuals. For natural selection to work, individual and its descendants must meet very similar events and interactions.

It can be assumed that individuals are stable patterns like waves existing in the discrete structure. Their origin may even be the topological curvature knots? The patterns should be resistant to perturbations. Presumably perturbations arise from reproduction and variation postulates of natural selection. The process starts from a very simple state of the structure. But the state of minimum complexity from which the process begins is still under consideration.

Presumably, the rules at the same time give rise to the structure that consist of interconnected atomic parts, and produce the natural selection of patterns in the structure. The structure is discrete and finite. Steps of time that correspond to changes in the structure, are also discrete. How is it that the pattern in the structure is the same as the individual in the natural selection? And the pattern and the individual are the same in that picture. May be the atomic parts in the structure similar to a graph are the atomic individuals.

And these atomic individuals easily increase their number. Then how do non-atomic individuals appear? So my question is a request for intuitions on how to create that complete picture that satisfies the constraints.

The two hardest problems I struggled and haven't solved are about 1 how to define fixed laws that govern structure change meta-laws? And even more: that two problems seem to be two sides of the same single problem.

From simple point of view we should not really expect to get all laws of nature from our particular real universe if we are to discover laws via natural selection modelling. But from the second point of view we should define laws of nature in a common way: the laws meta-laws? The guiding constraint of my research program is that the desired model should be the simplest to the point of being self-justifying.

That's important because I only have metaphysics philosophy considerations for this. And philosophy considerations should be obvious or close to it to be useful.

For example from philosophy point of view we can argue that the Universe should've had the simplest first state at the first moment of time 1: the World wasn't created this morning with me unshaven , 2: we do not hide behind infinite causal chain that goes back to the past like ancient Greek hide gravitation pull to the Earth behind infinite elephants that the great turtle rest on. Or that discrete countable infinite time and discrete finite space is preferable over uncountably infinite time and infinite space.

And Occam's razor presumption is quite good for justifying it. That's good but drastically not enough to build a math model. So we need to define these meta-laws that simple to the point of being self-justifying It's still possible to go with for no reason particular laws that are not self-justifying but with this we lose the only way of pure philosophy justifying.

And we also already do not have empirical justifying because if we are to go with natural selection thing then we should think that Lee Smolin's Cosmological natural selection hypothesis is likely to be true.

So our real universe would definitely be out of our modelling abilities even if we have the desired model formulated. So we have no choise but to define these meta-laws that simple to the point of being self-justifying. But at the same time the self-justification mentioned is based on my own sense of what should be done aesthetics of a brain - trained neural network. And it might be not enough to properly define and justify the initial hardcoded meta-laws that provide medium for natural selection to work on.

I believe some of that aesthetics are good to go and should not be revised as they are enough self-justified: like discrete time and space, the first "simplest" state at the first moment of time, incorporation of natural selection postulates in some way.

Rest of my aesthetics try to guide me how to add that. But problems arise Then try to strip as much from the model as possible and see if it's can be viewed as self-justifying from philosophical point of view. But it's a risky way as it The Open Boat Questions And Answers Google may be that we would not be able to strip enough to justify.


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