Can we make software that comes to life?

Is evolution about to enter a new phase? Today, 300 biologists, computer scientists, physicists, mathematicians, philosophers and social scientists from around the world are gathering in Winchester. Their aim is to address one of the greatest challenges in modern science: how to create a genuine artificial life form.


Is evolution about to enter a new phase? Today, 300 biologists, computer scientists, physicists, mathematicians, philosophers and social scientists from around the world are gathering in Winchester. Their aim is to address one of the greatest challenges in modern science: how to create a genuine artificial life form.

Intelligent design: self-aware computers such as Pixar’s Wall-E
are surprisingly tricky to put together

The idea that life owes its existence to some “vital essence” or “animating spark” has long been discredited in scientific circles. Instead, it is believed that the first living thing emerged after a chemical reaction crossed the watershed that divides inanimate objects from the kind of self-replicating “organic” reactions that run our cells.

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.

His conclusion? Although natural selection is necessary for life, something is missing in our understanding of how evolution produced complex creatures. By this, he doesn’t mean intelligent design – the claim that only God can light the blue touch paper of life – but some other concept. “I don’t know what it is, nor do I think anyone else does, contrary to the claims you hear asserted,” he says. But he believes ALife will be crucial in discovering the missing mechanism.

Dr Richard Watson of Southampton University, the co-organiser of the conference, echoes his concerns. “Although Darwin gave us an essential component for the evolution of complexity, it is not a sufficient theory,” he says. “There are other essential components that are missing.”

One of these may be “self-organisation”, which occurs when simpler units – molecules, microbes or creatures – work together using simple rules to create complex patterns and behaviour.

Heat up a saucer of oil and it will self-organise to form a honeycomb pattern, with adjacent “cells” forming as the oil turns by convection. In the correct conditions, water molecules will self-organise into beautiful six-sided snowflakes. Add together the correct chemicals in something called a BZ reaction, and one can create a “clock” that routinely changes colour.

At the Winchester conference, Prof Takashi Ikegami, from the University of Tokyo, will explain the ways that self-organisation operates among birds, to help them form flocks, and in robots, children, flies and cells, too. Another keynote speaker will be Prof Peter Schuster of the University of Vienna.

With the Nobel Laureate Manfred Eigen, he came up with the idea of the “hypercycle” – different components “feeding on each others’ waste” while maintaining an (often fragile) overall stability. This scheme was used to show how simple chemicals co-operated to create the first living things billions of years ago.

“Evolution on its own doesn’t look like it can make the creative leaps that have occurred in the history of life,” says Dr Seth Bullock, another of the conference’s organisers. “It’s a great process for refining, tinkering, and so on. But self-organisation is the process that is needed alongside natural selection before you get the kind of creative power that we see around us.

“Understanding how those two processes combine is the biggest challenge in biology.”


A simple single-celled amoeba has been turned into a computer by Drs Masashi Aono and Masahiko Hara at the Japanese research institute Riken. They harnessed the way that the creature responds to light to allow it to solve a famous puzzle called the travelling salesman problem.

The set-up is this: a sales rep has, say, six cities to visit. To minimise his travel costs, he must find the shortest route between them, one that visits every city just once. Once the number of cities grows to several hundred, the task will become too complex for even the cleverest computers.

In this case, the slime mould Physarum polycephalum solved the problem for four cities. The team harnessed two facts: the creature wants to have the biggest body area, but dislikes light. Thus they forced it to search for nutrients down specific branches – the routes between the cities – while it tried to minimise its exposure to illumination.

Hugo Marques of Essex University will discuss a pioneering attempt to give computers some imagination – which he believes “may be a significant step towards building a robot with a mental life”. He will try to mimic the relationship between the human brain and body by giving a robotic consciousness a skeleton to inhabit.

Scientists are also hoping to enhance our ability to study pollution and climate change by using “smart dust” – wireless chips with their own power supply and sensors that link to each other via radio. The Winchester conference will hear a proposal by Prof Davide Anguita and Dr Davide Brizzolara at the University of Genoa for a marine equivalent called smart plankton, which will provide “shoal intelligence”.

A new way to fight junk emails has been developed by Alaa Abi-Haidar of Indiana University and Luis Rocha of the Instituto Gulbenkian de Ciência, in Portugal. It is inspired by the way the body’s immune system fights off invading diseases and, according to Dr Abi-Haidar, promises greater resilience than existing systems to changes in the ratio of spam received compared to normal email (“ham”).

Roger Highfield

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Web pages have ‘come alive and started breeding’

Living web sites that grow, develop and evolve to suit the taste of the people that read them are now finding their way on to the internet.

Living web sites that grow, develop and evolve to suit the taste of the people that read them are now finding their way on to the internet.

For two decades, computer scientists have played around with evolutionary software that can gradually evolve and mutate to carry out a task efficiently, or hone the design of a wing, robot or whatever, without the need for a programmer to get involved.

A grouping of some of the sites with human controlled
design properties or genetic design evolution

Now these techniques are being used to allow web sites to keep themselves up to date and to adapt to the latest fads and fashion, reports New Scientist.

Not only are they quicker to evolve than possible with human intervention, they offer the chance to come up with new ways to organise material in the web that work best for users.

Matthew Hockenberry and Ernesto Arroyo of Creative Synthesis, a non-profit organisation in Cambridge, Massachusetts, have created evolutionary software that alters colours, fonts and hyperlinks of pages in response to what seems to grab the attention of the people who click on the site. See for more.

To start, he used mouse-tracking software developed by Arroyo while at the Massachusetts Institute of Technology on 24 people who were asked to use a basic web site template for a blog.

Once the blog went live, control of the design was out of their hands.

The software treated each feature as a “gene” that was randomly changed as a page was refreshed.

After evaluating what seemed to work, it killed the genes associated with lower scoring features – say the link in an Arial font that was being ignored – and replaced them with those from higher scoring ones say, Helvetica.

“We see a lot of terrible designs for the first 100 or so generations,” Hockenberry tells New Scientist.

But the pages gradually morph to be more pleasing. Interestingly, they do not simply reflect a consensus of what people want to see, since the random element means the exercise is truly creative.

“The mutations will always occur and while they are responsive to human attention, they are not bound by them.

It is possible to develop unique mutations that may actually influence human goals (rather than the other way around).”

Prof Gregg Vanderheiden of the University of Wisconsin-Madison, says sites that cater to people with disabilities would particularly benefit from evolving pages.

And evolutionary computing researcher Charles Ofria of Michigan State University in East Lansing says the idea might remove the need to constantly test websites on users in the way that companies like Amazon, Google and Facebook now do.

The work is reminiscent of the way that evolutionary methods were used to create organic art by the America Karl Sims – at an exhibition, art was continually evolving by breeding the images that people liked to look at, and killing those that were unpopular.

“A lot of the work done in genetic / organic art certainly serves as a significant intellectual inspiration,” says Hockenberry.

“The most significant difference is the goal of targeting the real public in a process. We want to add a sense of responsibility to this genetic growth. Does the process make sense? Does it do something useful? How do people work within this process and support it?

“Most of the examples of using genetic algorithms are about making something – and then showing the result for interaction. We want human creativity to be a driving force within a process of computer genetic evolution. So while pages might be growing – it still matters if humans take care of them and they can still influence the growth in very significant ways.”

Roger Highfield

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