Reverse engineering a front-loaded state

An article in the Telegraph asks whether we can make software that comes to life? A non-teleological viewpoint should predict that intelligence can evolve from simple precursors without some "vital essence" or "animating spark". It is interesting to note some of the research up to date:
Quote:

Researchers into artificial life, or "ALife", take two basic approaches. In "wet" ALife, scientists either tinker with microbes and other forms of simple life, or try to cook up cocktails of chemicals in water (hence "wet") that have the capacity to extract energy and raw materials from the environment, to grow and reproduce, and ultimately to evolve. Meanwhile, "in silico" ALifers use silicon chips to try to kindle the spark of life in the heart of a computer.

In the latter field, a celebrated experiment was carried out almost two decades ago by Dr Thomas Ray, at the University of Delaware. He created the first successful attempt at Darwinian evolution inside a computer, in which organisms - scraps of computer code - fought for memory (space) and processor power (energy) within a cordoned-off "nature reserve" inside the machine.

His evocative experiment was called "Tierra", after the Spanish for "Earth". Back in 1993, when I met him in Oxford, it seemed to be a vital tool in helping us understand why the world is seething with diversity, from rainforest to coral reef.

For evolution to occur, Dr Ray had to allow his programs to mutate. The "Tierran" programming language he devised was robust enough that it could often work after mutations. He also had natural selection: a program called the reaper killed off old and faulty software, enabling more successful organisms to monopolise resources.

On January 3 1990, he started with a program some 80 instructions long, Tierra's equivalent of a single-celled sexless organism, analogous to the entities some believe paved the way towards life. The "creature" - a set of instructions that also formed its body - would identify the beginning and end of itself, calculate its size, copy itself into a free region of memory, and then divide.

Before long, Dr Ray saw a mutant. Slightly smaller in length, it was able to make more efficient use of the available resources, so its family grew in size until they exceeded the numbers of the original ancestor. Subsequent mutations needed even fewer instructions, so could carry out their tasks more quickly, grazing on more and more of the available computer space.

A creature appeared with about half the original number of instructions, too few to reproduce in the conventional way. Being a parasite, it was dependent on others to multiply. Tierra even went on to develop hyper-parasites - creatures which forced other parasites to help them multiply. "I got all this ecological diversity on the very first shot," Dr Ray told me.

Other versions of computer evolution followed. Researchers thought that with more computer power, they could create more complex creatures - the richer the computer's environment, the richer the ALife that could go forth and multiply.

But these virtual landscapes have turned out to be surprisingly barren. Prof Mark Bedau of Reed College in Portland, Oregon, will argue at this week's meeting - the 11th International Conference on Artificial Life - that despite the promise that organisms could one day breed in a computer, such systems quickly run out of steam, as genetic possibilities are not open-ended but predefined. Unlike the real world, the outcome of computer evolution is built into its programming.

How about simulating a front-loaded state and let it evolve through random variation and selection? Front-load systems found in simple unicellular life into a "virtual single cell" (Figure 1).
the similarities between self-replicating cells and the proposed self-replicating program (Figure 1 vs Figure 2):
1) Core Coded Components:
Cells:

• Cell cycle machinery - Process of cell division
• Coded information - DNA, RNA, Proteins
• Quality Control Systems - Chaperones, DNA repair mechanisms, Programmed cell death

Self-replicating Program:

• Self-replicating code - Process of self-replication
• Coded information - Whatever software you are using
• Quality Control Systems - Checksum, Parser, Programmed Destruction of faulty self-replicators

2) Variable Coded Components:
Cells:

• Metabolome - Energy conversion
• Certain replisome components - Variable components to allow for optimization (polymerases)
• Cytoskeletal components - Structure holding the cell together
• Signal transduction components - Gathering of extracellular information and transducing it to be interpreted.

Self-replicating Program:

• Metabolome - Usage of resources E.g. memory, CPU, network etc.
• Self-replication Code - Variable components to allow for optimization
• Code structure - Variability of syntax and code language etc.
• Signal transduction components - Interaction with other self-replicators and resources.

3) Variability inducer:
Cells:
The immune system purposefully induces mutations through the activity of cytosine deaminases and incorporate low-fidelity repair systems to allow for variability. Thus, the immune system harnesses random variation and natural selection to produce antibodies to ward off harmful organisms.
Bacteria also have cytosine deamination enzymes as well as low-fidelity repair systems.

Self-replicating Program:
Perhaps program a similar "variation inducer" that is activated under time of intense selection pressure in order to make more use of randomness to generate variability. Incorporate this system to work with the quality control systems.

Figure 1: Core components of cells.

Figure 2: Core components of virtual front-loaded self-replicator

Simulate the evolution of these virtual front-loaded organisms. To really complicate the simulation, throw in a few quantum computing structures (tubulin, Ftz-like perhaps) and simulate an environment that is composed of elementary particles. Simulate these elementary particles to have two aspects. Physical and phenomenal. The physical aspects govern the simulation in a deterministic way. The phenomenal aspects are composed of elemental proto-experiences (PEs). Simulate the phenomenal and physical aspects to be irreducible fundamental properties that exist in superimposed form.

Who knows, maybe an explosion of simulated complex life will be observed after structural components evolved to interact with these PEs?

A prediction a front-loaded state would be that intelligence will evolve in cyberspace. Off course it is the same prediction as the non-teleological view. If it does turn out that the front-loaded state better explains the evolution of life, all that needs to be explained is the evolution of the front-loaded state through abiogenesis.