Greg Detre
Friday, October 06, 2000
His premise was that �the basis of life is information, steeped in a dynamical system complex enough to reproduce and bear offspring more complex than the parent� (Levy). He also recognised that genetic information has two roles: as a record to be carried and transferred (genotype) and as a recipe used to physically build the organism (phenotype). He imagined a creature constructed from girders in a lake, which carried the information to replicate itself in its physical structure (a tail-like component, analagous to DNA), which it processed like a Turing machine.
With Stanislaw Ulam???, he devised cellular automata (CA). These are a grid (1- or multi-dimensional), and each cell is in one of a set of states. Proceeding in discrete time steps, the state of each cell is affected by its neighbours.
Considered a huge landing party comprised of self-replicating robots that would colonise the moon at miniscule cost (akin, I suppose, to Arthur C Clarke�s exponential monolith expansion which exploded Jupiter).
Computer animator who watched geese and birds flocking, realised and realised that it could be recreated without a centralised controlling mechanism but would emerge from a simple, local and reactive algorithm followed by each bird. Created boids, and showed them actually flocking round a pair of columns, using just 3 simple rules:
Conway wanted to demonstrate that a CA could act as a univeral computer. In the Cambridge Maths Department, used a huge sprawling Go set to run his games of �Life� (a 2-dimensional binary CA) by hand. He needed a pulse generator, which fired out gliders, to represent the bits, so he posed the problem as a Scientific American maths enigma. Gosper at MIT wrote a Life program to produce puffer trains which produced glider guns � Conway was also able to represent logic gates and internal storage, and demonstrate that that Life could perform universal computation.
Saw the connection between the chaotic triangles of one-dimensional CAs and the patterning on a natural mollusc shell. Also categorised his CAs into 4 classes: fixed, periodic, complex and chaotic.
Pushed the �bottom-up� approach. Managed to get his little tear shapes to replicated themselves, despite their basic structure and procedures. Organised the first A-life conference. Building on Wolfram�s four-fold classification scheme, he introduced the variable lambda (l) as a measure of the chaos in a life model. Showed that life thrives on the phase transition border between too much chaos and too much order - complexity.
Believes that we need to be open and think now (admittedly prematurely) about the implications of successful a-life research � perhaps the only reason that a-life has not attracted the level of public concern it may one day deserve is that few believe it to be possible.
Attacked the problem of life with the paradigm of self-organisation. Used a 100x100 CA (modelled using computer time on an IBM mainframe) with lots of rules relating the neighbouring cells together, known as the Kauffman Model. Within a few steps the model looped (showing simple self-organisation), and it didn�t matter what the initial state of the cells were. This showed that the details and random starting point of the network were not important, since the overall self-organising structure of the whole network dealt with them anyway. Hence the robustness of our DNA, which is filled with mutations and mistakes.
Contributed to the chicken-and-egg debate about RNA molecules and metabolism. His theory (apparently similar to Eigen�s �hypercycle theory�) did not place one first without the other, but showed how a single RNA molecule might also handle metabolism???
VENUS � virtual evolution in a non-stochastic universe simulation � attempted to model the emergence of life in a prebiotic soup by tweaking the physical/chemical parameters
Rasmussen�s contentious �Aspects of Information, Life Reality and Physics�, distributed at the second A-life conference:
1. A universal computer is indeed universal and can emulate any process (Turing)
2. The essence of life is a process (von Neumann)
3. There exist criteria by which we are able to distinguish living from non-living things
Accepting (1), (2) and (3) implies the possibility of life in a computer
4. If somebody manages to develop life in a computer environment, which satisfied (3), it follows from (2) that those life-forms are just as alive as you and I
5. Such an artificial organism must perceive a reality R2, which for itself is just as real as our �real� reality R1 is for us.
6. From (5) we conclude that R1 and R2 have the same ontological status. Although R2 in a material way is imbedded in R1, R2 is independent of R1.
7. If R1 and R2 have the same ontological status, it might be possible to learn something about the fundamental properties of realities in general, and of R1 in particular, by studying the details of different R2s. An example of such a property is the physics of a reality.
Rasmussen was quoted as saying that �in his heart of hearts�, his investigations of a-life are �wrong�.
At IBM???, wrote the champion checkers program, using GA techniques.
First computer science PhD. Believed in and demonstrated the greater importance of crossover than mutation. Seeking to harness the �perpetual novelty� of evolution to produce �something from nothing�. With his students, he designed number-sorting GAs which produced his phone number etc.
Rev. William Paley �he didn�t see how nature (the �Blind Watchmaker�) could evolve organisms as intricate as those which do exist � if one stumbled across a clock in a field, one would take that as evidence of a �watchmaker�
Produced lots of little GA ants to navigate a �scent� (full of gaps and twists), a.k.a. the �John Muir� ant trail. In about 70 generations, there were populations composed mostly of perfect ants which had learned tricks to manage all 89 moves through the trail in the allotted 200 time steps
In the �Blind Watchmaker�, Dawkins wrote a program which uses 9 �genes� (e.g. symmetry, segmentation, branching) composed of 19 alleles to produced tree-like figures on the screen. The human observer hand-picked from the offspring, usually on aesthetic grounds, and led to realistic looking insects, trees and structures.
Organisms within Tierra fought for CPU cycles within a virtual machine, keeping themselves small and altering each other�s codes parasitically to reproduce themselves.
Brookes� vision of building up to intelligence incrementally, first through robust, non-cognitive attempts like Genghis and Attila (designed as a potential Mars or lunar lander).
Former MIT student, founded the Connection Machines Corporations(???) which marketed powerful, massively parallel computers (< 65,536 processors), as well as tinkering with his own Ramps a-life. Realised the importance of predators/parasites in shifting GAs from local maxima and increasing robustness and efficiency. His GAs came close to besting all human attempts at number sorting algorithms.
Is amongst those who believe that strong a-life is inevitably on the cards, and that it may ultimately replace us. Is not dismayed by this, so long as our artificial successors inherit our ability to love, create and think.
A 100x100 grid with agents (with primitive neural networks and the capacity to evolve), carnivores, trees, plants and rocks. Demonstrated the Baldwin effect, as well as discovered a potentially new evolutionary idea, �shielding�, whereby a useful evolved trait undermines the neural net�s learning.
Xerox PARC researchers who released the first worm onto the Xerox ethernet at night to perform various functions, paralysing the whole network at one point, as part of a vision of distributed computation.
A UCLA biologist who worked with Jefferson, pointed out that self-evolving a-life would inevitably violate Asimov�s First Law of Robotics.
First conceived of the idea of computer viruses, probably the strongest contenders for the Strong Claim to a-life. According to Doyne Farmer and Alletta Belin, a virus �satisfies most, and potentially all, of the criteria [for life]�. A computer virus:
o is a pattern on a computer memory storage device
o can copy itself to other computers, thereby reproducing itself
o makes use of the metabolism of its host (the computer), like a real virus, to modify the available storage medium
o senses changes in the copute ran responds to them in order to procreate
o its parts are highly interdependent
o is robust enough under small noise fluctuations, though not large electrical perturbations, and sometimes under small alterations in its instructions and programs
o evolve to a limited degree, though usually through human intervention, to adapt to new environments or make themselves harder to detect and eliminate
Most frighteningly, viruses show that the step to being the victims of autonomous creations is possible, and that we may not be able to simply �pull out the plug�.
Viruses highlight the flaw in the belief that life somehow transcends the Second Law of Thermodynamics (that of order ultimately giving way to disorder), in that life pays the price of generating order in terms of a massive disordering of the environment around it.
Wrote a system which used a set of viruses communicating with each other, lying dormant and performing garbage collection-like duties which ran stably for 2 years as a demonstration of harnessed viruses� potential benefits. Sponsored a $1000 annual for �the most useful computer virus�.
Wrote a �liveware� (virus-based) technology, where a communal database kept itself continually updated across a number of computers by �enlivening� the data to inform other copies of changes.
One of the early victims of Cohen�s Brain virus, argues strongly that the scientific study of viruses is immoral, prompting the debate about a-life as being the nuclear bomb of the next century, a scientific leap that we are ill-prepared to handle. As Langton points out, the burden of responsibility for the technology of death is potentially outweighed by that of creating life.
Argues against AI, though retracts this when discussing AI as evolved from a-life attempts, conceding that there is something extraordinary about the process of evolution which cannot be discounted.