ECAL session notes: Digital Evolution

As before, what follow is a very slightly cleaned up version of the notes I took during the second ISAL summer school session at ECAL 2017. Also as before, note that this is very rough, made while I was reviewing them tonight. Apologies for any typos or other mistakes.

Digital Evolution

Charles Ofria, Michigan State University

Before the talk started there was a bit of discussion about the previous talk, on historical and philosophical perspectives on artificial life - specifically on the conclusions reached about Tierra in the last talk, with which this speaker somewhat disagreed. In the previous session it was concluded that Tierra does not go on to confirm the arrow of complexity hypothesis because plenty of programs in that simulation became smaller rather than growing. However, Charles Ofria points out that apparently if you add more “good” factors than just speed of reproduction, the programs do grow. But, as I also wondered in the last talk, does a larger program size really indicate a greater “complexity”?

Anyway, to move on to the actual talk:

The more the speaker learned about AI the more he realized “true” AI was 10-20 years away…like it has always been and is now.

Evolution is hard to study. Living organisms:

What can we do to overcome these challenges? If we could study this in a computer, the above problems all become more manageable (but not necessarily completely avoidable)

Digital Organisms

What are digital organisms?

Digital Organisms are computer programs that self-replicate and can evolve to thrive in a noisy computational environment. Some properties/benefits:

If we want to learn about evolution as a process we need an open-ended evolving system where organisms can interact and alter their environments.

The notion of “digital organisms” came from PC game “Core War”. Players are programmers who write code and put it in memory of a PC (nowadays virtual). Programs try to shut each other off. The last program standing wins.

One of the really consistent approaches to Core War was to write a program that made a copy of itself first, and then did whatever else it was going to do. This way if you get shut off you have copies to continue the fight. It was sort of reminiscent of living organisms, but an issue with Core War was that there was no source of variation in the system. You do not observe any kind of evolution.

In 1990, Steen Rasmussen built VENUS. With VENUS, aka Core Worlds, he was able to see stable, cooperative code structures arise, but no proper self-replication. Core Worlds was similar to Core War, but added mutations into the system. Self replicators would break down because of the mutations. A broken organism would start writing all over the place in memory and killing everything around it.

In 1991, Tom Ray designed Tierra. It based on Core War but with mutations as a source of variation. He made digital organisms write protected so they couldn’t just write over each other. So you could no longer trivially kill each other as in Core World.

Tierra overview:

Evolution in Tierra progressed in two different directions:

One pressure was for programs to shrink. Since the shorter the program is, the less it has to copy the faster it can copy itself.

Second pressure: parasites would appear. This was very puzzling at first. Parasites were much shorter programs that started taking over the population, but failed to completely do so and died out, but then started taking over again, displaying an oscillation in parasite vs non parasite population. Parasite programs were almost identical to fully functional program structure - they would go as far as allocating space but instead of having a copy loop it would find another program nearby to use its copy loop. But when parasites started taking over the population there were too few programs with proper copy loops and the parasite population would shrink once more.

Eventually full programs started writing traps for the copy loop - instead of letting a parasite copy it, it would copy the host program. In this way a slightly longer program could be successful as it had a clever “hyper-parasite” strategy. For the most part though the programs ended up getting shorter.


Avida is inspired by Tierra

Avida vs Tierra

Comparisons to Experimental Evolution

Example: a pair of competition experiments.

Two environments.

Yellow organisms from Env A are put into Env B with blue organisms and vice versa. Usually organisms which evolved in particular environment do better in that environment than the newly introduced organism; in about 25% the newly introduced organism ended up winning, because during these experiments further evolution can be occurring that can swap favor.

Tracking evolution in a digital world:

With digital organisms we can look at any aspect of the population over time.

Avida digital organisms are set up in such a way that we can do the sorts of experiments biologists will often perform, but in a much more automated and simple fashion. Eg: knockout experiment (knocking out a gene to see what happens to a trait/operation) came from biology.


Unlike in Tierra, parasites do not evolve spontaneously in Avida. Parasites in Avida are more like “cheaters” - they replicate faster but do not hurt the host (they do hurt everyone around them). A parasite is a piece of code that just steals CPU cycles from a host vs directly harming the host.

A parasite commonly injects itself by targeting a particular task the host is doing to infect the organism that is doing that task. Even if all tasks are made equally valuable, hosts evolve to do more and more complex tasks requiring more code because if it’s more complex for the host it is also more complex for the parasite - the presence of parasites drives up the complexity of the host.

Comparisons to behaviour studies

We can examine behaviours evolved by digital organisms, such as foraging startegies.


Sexual replication

The experiments shown in this presentation all had the organisms reproducing asexually. A question was asked about whether anything had been done with sexual reproduction. And in a limited way, yes; so far the observations have been:

© - 2021 · Liza Shulyayeva ·