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I believe the problem is with ever advancing hardware. The new chips are much faster and would "overtake" an experiment that's been running. This problem is so

by bh23ha 17y ago

I believe the problem is with ever advancing hardware. The new chips are much faster and would "overtake" an experiment that's been running. This problem is sometimes described as putting colonists on a space ship and sending then off. They travel for generations but before arriving they are overtaken by another ship which started several generations later, but was much faster because technology back on Earth kept advancing. Then there's the problem with convergence. Even on a scale as large and complicated as Earth creature often reach an adaptive maximum which tends to keep them the same until an external shock. Think sharks, or punctuated equilibrium. In a computer the simulation will also quickly reach a maximum and there's only so large and complex a simulation can be before you're talking crazy money for the machines. Without crazy money the simulation could hardly be complex enough to keep evolving for ever. Obviously we have game-of-life like algorithms which can generate new patterns for ever, but they are not under selective pressure.

jsolson 17y ago
> I believe the problem is with ever advancing hardware. The new chips are much faster and would "overtake" an experiment that's been running. There's no reason why this would have to be a problem. It should be possibly at any given iteration to take a snapshot of the population and transfer it over to new hardware. One could even consider experiments in which you periodically scaled the population up to utilize an order of magnitude more computing power (to increase diversity in a population that had converged to some local optimum) and then scaled it back down to some randomly selected subset once sufficient divergence had occurred. Since computing resources can be purchased in small discrete units these days, this might even be a viable method to reduce overall search cost.
kbob 17y ago
Here's a physics paper that analyzes that question. It's a joke paper, but the conclusion is valid (subject to various simplifying assumptions). Their conclusion is that if a computation takes over 30 months to complete, you're better off waiting for faster hardware. http://arxiv.org/abs/astro-ph/9912202 http://arxiv.org/abs/astro-ph/9912202 The Effects of Moore's Law and Slacking on Large Computations Authors: C Gottbrath, J Bailin, C Meakin, T Thompson, J.J. Charfman We show that, in the context of Moore's Law, overall productivity can be increased for large enough computations by `slacking' or waiting for some period of time before purchasing a computer and beginning the calculation.

by bh23ha 17y ago

jsolson 17y ago

> I believe the problem is with ever advancing hardware. The new chips are much faster and would "overtake" an experiment that's been running. There's no reason why this would have to be a problem. It should be possibly at any given iteration to take a snapshot of the population and transfer it over to new hardware. One could even consider experiments in which you periodically scaled the population up to utilize an order of magnitude more computing power (to increase diversity in a population that had converged to some local optimum) and then scaled it back down to some randomly selected subset once sufficient divergence had occurred. Since computing resources can be purchased in small discrete units these days, this might even be a viable method to reduce overall search cost.

kbob 17y ago

Here's a physics paper that analyzes that question. It's a joke paper, but the conclusion is valid (subject to various simplifying assumptions). Their conclusion is that if a computation takes over 30 months to complete, you're better off waiting for faster hardware. http://arxiv.org/abs/astro-ph/9912202 http://arxiv.org/abs/astro-ph/9912202 The Effects of Moore's Law and Slacking on Large Computations Authors: C Gottbrath, J Bailin, C Meakin, T Thompson, J.J. Charfman We show that, in the context of Moore's Law, overall productivity can be increased for large enough computations by `slacking' or waiting for some period of time before purchasing a computer and beginning the calculation.