The Computer Maverick Who Modeled the Evolution of Life (2014)
m.nautil.us
m.nautil.us
There's no mention of Barricelli though, but another equally interesting book [2] recognizes his pioneering work on artifical symbiogenesis (and that was back in 1953!), and speculates on its importance in the genealogy of computer worms and viruses.
A bit from a month ago: https://news.ycombinator.com/item?id=20439790
- Cellular Potts Models
- Evolution of evolvability
- Replicators and the Error treshold
https://www.amazon.com/Introduction-Evolutionary-Informatics...
As far as I can see, the point made in the (first part of) the book is that informed algorithms (on average) always outperform random searches and that genetic algorithms are akin to random searches.
The first part is true, the second part isn't. Evolution isn't random, mutation is random. Selection is very much not random, it is informed by the environment. This drastically reduces the size so-called "search space".
Using the term "search" for the outcomes of evolution is a curious choice anyway. Evolution doesn't search for anything in particular, it produces adaptation to an environment. It's a process without end.
As for computer simulations, check out the simulated biped that evolved hopping like a kangaroo:
The fundamental point is that information is conserved, so if artificial life sims produce information, it must have been inserted into the code at some point, and it is possible to track down these particular insertion points, which the authors do. In information theory the conservation of information theorem goes by various names, such as the data processing inequality and independence conservation.
Anyways, I highly recommend the book. Everything is clearly laid out for your own analysis and application.
Fair enough. Let's apply this to the video I linked. The authors certainly didn't add "information" about what walking or hopping looks like into the code explicitly. It just emerged. Following your logic, the hopping behavior can't be new information, it must've been contained in the rules of the simulation.
The simulation itself is made up mostly of an off-the-shelf physics library, a couple of muscle-skeleton arrangements (authored by hand), and a fitness function measuring the distance traveled by activating those muscles through weights (the learning variables). Given this environment, walking, hopping and running behaviors invariably emerge. Fascinating!
Adapting this to our world, the laws of physics and the initial arrangement of matter contain all the "information" required for life to eventually emerge in the universe. This leaves you with a "god of the gaps" opportunity: An intelligent designer must've designed those laws and made that arrangement of matter so that it all works out. This is however entirely compatible with Darwinian models.
I don't have an issue with that kind of hypothesis, except that it is unclear what the existence of such a god/designer would imply for our particular lives here on earth.
Not really, like I said, there's usually better algorithms than genetic algorithms. They're fun to play around with, though.
> It also seems you think that evolutionary algorithms are somehow analogous to biological evolution. To what degree do you think that is true?
The general principle - selection and random mutation - is the same.
Also, I am surprised you've followed this discussion for so long. Most people fire off some canned phrases and then disappear.
Do I sound confident about them? I've said multiple times that they usually aren't very good and that usually you have a better algorithm. Usually, you can apply intelligent design.
The fundamental difference between us is probably that you'd look at life in nature and say something like: "This species is so remarkable, it must've been designed!".
I wouldn't jump to that conclusion. It's only remarkable if it emerged naturally. If it was designed, then I would have to point out all sorts of obvious flaws in the design.
Regarding GAs, the conservation of information applies to how much information we can expect from a single random sample. If we can sample from the entire space of possible solutions, then there is a chance of sampling the optimal solution. The conservation of information applies to the necessary input to the algorithm in order to bring the chance to a certain level.
Of course I am, just like you assume "materialism" on my part. I have trouble believing that you're not an ID proponent, even though you're not upfront about it. Otherwise, why bring up books by people with a clear ID agenda?
I'm honestly not sure what your goal is here, anyway. You rarely address any questions that I ask. Making assumptions is all I can do.
> I said Darwinism appears to be completely useless when it comes to practical application, and has been replaced by other mechanisms that are identified in the biological data.
You actually called Darwinism "quackery" and said that it is "dead". This is the least strong version of your position so far.
I don't disagree that Darwinism, in the sense that it describes the origin of species, has no direct practical applications. Nobody is in the business of simulating entire ecosystems for thousands or even millions of years. Using that fact as some sort of criticism of the theory itself seems rather hamfisted.
> Regarding GAs, the conservation of information applies to how much information we can expect from a single random sample. If we can sample from the entire space of possible solutions, then there is a chance of sampling the optimal solution.
Fair enough, but GAs are awful for finding the optimal solution. However, nature doesn't require the optimal solution. It just looks for the next best thing, over and over. GAs tend to converge to some level of fitness and stay there.
In fact, it's likely that a random algorithm outperforms those GAs that can get stuck in local maxima. Again, this has no bearing on nature. Nature is fine with local maxima.
Fair enough, I was looking to continue where we left off in the other thread.
> I think it will confuse the discussion to try and bring in biological evolution and intelligent design. I've researched GAs and information theory to a fair extent, and am happy to answer questions and discuss on that topic.
Again, that's fair enough. However, if we're leaving out biological evolution, I don't think there's much of an argument to be had.