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/--, `-' `-^ `-' `-^ 'Surely it should be the Flying Spaghetti Monster. <reaches for his steel colander>JoshParnell wrote:Hmm...Sr Giant Squid Monster...perfect! I was trying to figure out what the top rank should be.
Well, I don't use spinor fields in the game I'm afraidIndicable wrote:If Scalar Field is the highest rank, then I shall be the Spinor Field. (yeh, go ahead. soil your drawers)
By the way, in my opinion, I think its a bad idea to use scalar fields as a medium for simulating most physical processes. I don't get why people are trying to come up with new algorithms in that sort of area. That's just asking for lots of unnecessary derivation. Haha, I remember implementing collisions directly with a height map (for a terrain thingy). Waste of time. Also, If you have a fractal noise function, isn't it a good idea to use the 'fractal itself' virtually as a medium to accelerate propagation of effects in a dynamical field?
So it would be a lie! Maybe that rank should be reserved for future use...
I, Sir, have had several speculations in my pants... I'm not going to rant about them again... I need to grip more to explain my ideasI can't imagine any other concept that could unify all these things.
Meh. Dimensionality can be good sometimes. I guess you're right in this case, though. I really favor a single collisions implementation over specializations. OH YOU, ADDING COMPLEXITY LIKE AN EVIL SIR. (teasing you)Simplifying dimensionality of collision checking from 3 to 2 is a pretty big win!
False. False false false.but it's also the way the real world works.
From what I understand, it's generally just like n-dimensional arrays of various units; anything from a bitmap, to a planar fluid simulation or a light propagation volume.Wish I understood *fields theory
'Not difficult to wrap your head around.George The Sailor wrote:a scalar field associates a scalar value to every point in a space.
P.s. Oh, I guess I am ranting about this. Btw, I somewhat mentioned this concept when talking about fractal noise two posts ago.Me wrote:I'm interested in establishing a framework to dynamically reduce explicit/classical representations into various orders of abstraction with intent to simplify computation necessary for the simulation of systems. If you prefer that I specify how I imagine these systems might be, consider a very large set of points which may exhert various forces upon each other (classically, like particles) within the system e.g. exhibits contact dynamics and supports modelling external forces and fields from outside the system of points. Consider a large number of these points behave like a fluid, and they're contained in a way that can be approximated using a planar-surface fluid approximation method. I haven't researched these enough yet (planar fluid approximations), but I think it's an interesting idea to explore means to adaptively approximate systems using poweful mathematical generalizations. Of course, this particular type of fluid approximation I just gave for example is very limited (planar), but that's why I'm interested in adaptiveness; specifically a broad framework of malleate abstraction devices that can effectively perform these adaptations.
I like to think of this strategy like the theme of the book "A Wrinkle In Time"; virtually traversing spacetime by welding two points together into one. Rather than brute forcing the simulation, congruences may be identified (transitive actions, linear dependence, fractal phenomena etc.) to yield shortcuts and inherently simplify computation. You may call this an adaptive model or approximation.
I'm thinking of some kind of "tensor automaton, " if you can imagine what I mean by that (think of an intelligent lego sculpture). Are you aware of any ideas or do you know of information that is relevant and maybe interesting to this topic? Please discuss your thoughts.
"I, Sir, have had several speculations in my pants... I'm not going to rant about them again... I need to grip more to explain my ideas
(blip: Tensor Automatons -- not exactly fields -- is the name of one of them, probably the most relevant one)
Well, no need to rant, but it's hard to argue against something that one cannot see 
When you've formulated your ideas, we can discuss them concretely I suppose?Oh no I completely agree with you, I avoid specialization at all costsMeh. Dimensionality can be good sometimes. I guess you're right in this case, though. I really favor a single collisions implementation over specializations. OH YOU, ADDING COMPLEXITY LIKE AN EVIL SIR. (teasing you)
Just saying that, realistically, heightmap collision can be substantially accelerated by taking advantage of its structure. But personally I probably wouldn't specialize it either, for the sake of generality.Right now it's using a triangle-based algorithm, but I will probably change it later to directly use the fields so that it can run on the GPU. Mathematically, unified collisions under a field is absurdly simple: two functions, f and g, find x such that f(x) = g(x) = 0. Nice!Oh, is your collisions engine voxelizing meshs and using 'le voxels? I guess that'd be unified collisions with a scalar field.
Well you're going to need to elaborate a bit, because wikipedia, the ever-present argumentative force, is one my side...(http://en.wikipedia.org/wiki/Electric_potential http://en.wikipedia.org/wiki/Gravitational_potential). Sorry, I'm not trying to insult your intelligence by linking articles to potential..but without explaining your objection...it's the best I can doFalse. False false false.
It sounds great, but I'm not sure how it is relevant to the applications to which I've spoken of applying fields. You're speaking of simulating systems, I'm speaking of using fields as mechanisms to define and control a behavior (i.e. a surface, a collision interaction, AI movement, etc). I'm not seeing the conflict of ideas? There is no large-system simulation involved in any of the applications I've mentioned. Really, I'm just talking about the underlying representation of the algorithms used in the game, and how a unified representation can be exploited to certain ends. But if you have a better representation, I'm all for it, but it sounds as though you're speaking of developing accelerators for computing interactions, which is not really what I'm doing.Me wrote:I'm interested in establishing a framework to dynamically reduce explicit/classical representations into various orders of abstraction with intent to simplify computation necessary for the simulation of systems. If you prefer that I specify how I imagine these systems might be, consider a very large set of points which may exhert various forces upon each other (classically, like particles) within the system e.g. exhibits contact dynamics and supports modelling external forces and fields from outside the system of points. Consider a large number of these points behave like a fluid, and they're contained in a way that can be approximated using a planar-surface fluid approximation method. I haven't researched these enough yet (planar fluid approximations), but I think it's an interesting idea to explore means to adaptively approximate systems using poweful mathematical generalizations. Of course, this particular type of fluid approximation I just gave for example is very limited (planar), but that's why I'm interested in adaptiveness; specifically a broad framework of malleate abstraction devices that can effectively perform these adaptations.
I like to think of this strategy like the theme of the book "A Wrinkle In Time"; virtually traversing spacetime by welding two points together into one. Rather than brute forcing the simulation, congruences may be identified (transitive actions, linear dependence, fractal phenomena etc.) to yield shortcuts and inherently simplify computation. You may call this an adaptive model or approximation.
I'm thinking of some kind of "tensor automaton, " if you can imagine what I mean by that (think of an intelligent lego sculpture). Are you aware of any ideas or do you know of information that is relevant and maybe interesting to this topic? Please discuss your thoughts.
I will refute you with one word: Incompleteness. Suck it!Well you're going to need to elaborate a bit, because wikipedia, the ever-present argumentative force, is one my side...
Yes, I understand the difference.There is no large-system simulation involved in any of the applications I've mentioned.
What's the magic secret sauce you mentioned on your blog? haha, please don't tell me it's spatial hashing.Right now it's using a triangle-based algorithm
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