Digital Ecosystem, designed to simulate billions of years of evolution. Essentially start with limited, instruction-based code that updates itself incrementally, and let these separate programs interact with each other.
Do you think this would be a viable course of action for Artificial Intelligence? If not, why not?
Regards,
Jonathan"
On the sliding scale of simulated evolution there's the purely organic abstractions and ones that rather closely resemble a collection of programs with an over-watch breathing down their neck to keep the population in check.
I remember messing around with this sort of thing in passing; Truly fascinating. For reference the program I believe I used back in the day was Tierra, an early 1990's approach at the latter; evolution of programs competing for CPU cycles and memory space.
The people who worked with Tierra found some rather interesting approaches at maximizing their chances of survival and breeding came about; For example there where parasites that used other programs replication code to breed, counter-parasites that tricked the parasites to create copies of said counter-parasite and other fascinating things.
Newer similar projects have the individual programs gaining bonuses for completing certain tasks and the like.
So what about other means, like the one alluded to in the quote?
What I have described above isn't really meant to go anywhere specific, it's more about the journey. Another way of using evolving programs that is used today is about the end.
In this approach you start with a blank section of code, or write a set of code that conforms to certain functionality requirements. Then throw the original version through the blender a couple of times. Test if the 'offspring' are any closer to a second more constrained set of functionality requirements, take the winner(s) then rinse and repeat.
And then there's the viability thing...
There is only one major limitation to all the above examples: the environment. Processor, Memory, and the fact that we are only processing abstractions of biologically similar systems.
With an unlimitedamount of monkeys banging on typewriters processor power/memory, along with sufficiently complex methods of abstracting the biology in question (eg. enough potential complexity in the machine code of tiera or a good-enough facsimile of biological and/or neural function), we could very make a fully fledged AI - or in all likely hood - an entire ecosystem of them with a bunch of monkey equivalents with oppose-able thumbs sitting at the top.
And how long did it take to make humans, out of how many planets?
And then there's the viability thing...
There is only one major limitation to all the above examples: the environment. Processor, Memory, and the fact that we are only processing abstractions of biologically similar systems.
With an unlimited
And how long did it take to make humans, out of how many planets?
That is not to say we can not learn a ton from these systems. They are invaluable when it comes to learning about biological and digital evolution. In the far flung future we may well see an AI arise from a long forgotten simulation left running.
First generation of AI however will not be from the evolutionary department, it will be from the engineering department. That is not to say adaptive techniques developed by both the humans making the simulatee's - and the simulatee's themselves may well be finding their way into future (or even the first) generations of AI.
Now after all that I have to say it: Lets just hope whatever machine that is running our own universe isn't running windows!
First generation of AI however will not be from the evolutionary department, it will be from the engineering department. That is not to say adaptive techniques developed by both the humans making the simulatee's - and the simulatee's themselves may well be finding their way into future (or even the first) generations of AI.
Now after all that I have to say it: Lets just hope whatever machine that is running our own universe isn't running windows!