4 ms·
What about a decision like “can this wave be faithfully represented by this set of points?” Wouldn’t the Sampling Theorem give an answer in some bounded time?
by l33t2328 4y ago
What about a decision like “can this wave be faithfully represented by this set of points?”
Wouldn’t the Sampling Theorem give an answer in some bounded time? Is the idea that the time required to crank the algorithm can grow without bound?
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- Kranar 4y agoI feel like Buridan's Principle is either poorly worded, or most likely I just completely fail to understand it. The principle says: "A discrete decision based upon an input having a continuous range of values cannot be made within a bounded length of time." But certainly I can make a discrete decision in a constant amount of time, just choose to always go left. I must therefore be missing something here. The next possibility is that a discrete decision procedure that guarantees success is not possible in an unbounded amount of time. This is more sensible and I think the idea is that there will be some kind of infinite regress. For example a donkey will starve to death if it doesn't eat in exactly 100 seconds. The donkey can choose to walk left X meters, or walk right Y meters to some food. There are certain values of X and Y where the donkey dies no matter what, if X and Y are sufficiently far away that the donkey can never get to them in 100 seconds then the donkey dies. There are also certain values of X and Y where the donkey can pick either of them and survive since the donkey can get to X or Y in well less than 100 seconds, so the donkey lives. The above two scenarios are boundary conditions of sorts, where it's fairly trivial to come to a decision, the principle is about what happens when there is a value of X where it takes almost exactly 100 seconds to get to X, (and assume way more than 100 seconds to get to Y), but in order for the donkey to come to that realization the donkey needs to spend some time thinking about it and by the time the donkey has made a decision the donkey won't have enough time to carry it out. So the donkey has to take into account not only the amount of time to get to X, but also the amount of time it takes to come to a decision to get to X, but that too takes some finite amount of time... so the donkey has to take time to come to a decision about how long it takes to come to a decision to get to X, so on so forth... and you end up with an unbounded amount of time. I could be way off here but I feel there is some subtlety in the way this principle is described that I'm missing.
- worik 4y agoMy guess without looking it up.... > "A discrete decision based upon an input having a continuous range of values cannot be made within a bounded length of time." "A discrete OPTIMAL decision...."
- kevhito 4y agoThe missing piece of "just choose to always go left" is that this is a degenerate and uninteresting case. No decision is being made. The range must be discrete and at least 2 possible values. There is nothing about optimality at all here. Even if both possible outputs are equally "optimal", there is no procedure to pick one in a finite amount of time.
- Kranar 4y agoI doubt the issue has anything to do with being interesting or not. Do you know this for a fact or can give me anything to follow up on what it means for a decision to be interesting? For example if a decision procedure required the choice of chocolate or vanilla depending on the current time of day (a continuous input resulting in a discrete output), and I present an algorithm that categorically chooses chocolate regardless of what time it is, I doubt you'd turn around and claim that my algorithm is not making a decision because it always chooses chocolate. If an algorithm takes an input, continuous or discrete, discards that input and returns a constant value, that algorithm is just as "legitimate" as any other algorithm in so far as being an algorithm is concerned. It may not produce the optimal output for some given cost, but it is a formal and rigorous decision procedure that manages to output a discrete value given a continuous input in a bounded amount of time. At any rate, reading the comments when this was last posted it looks like the issue has to do with producing the optimal output in a given time frame. If an optimal discrete decision must be made in the next T seconds on the basis of a continuous input X, then there always exists some value of X that requires more than T seconds to compute. This will be true for any value of T regardless of how large.
- andi999 4y agoYes, always go left (except if you start at 1) is a solution. It is dismissed by Lamport though because the function is not continuous in 1. Somehow he believes not beiing continuous violates some principles of physics.
- gryn 4y agothe signal needs to have a maximal frequency for samling theorem to be aplicable. not all functions on a continious domain have that, in fact i think its the oposite most don't unless proved otherwise.