Tag Archives: replication
Avida
Self-replicating programs have been around for a while. The idea was first conceived by John Von Neumann in 1948 as a thought experiment. The first real instance was a game called Core War developed in the early 80s where programmers would write code to compete for sections of the computer’s memory. The best strategies were those that copied themselves, but these programs were fragile – change one piece of code and they would would cease to function.
Tom Ray’s Tierra in 1991 added some stability to the concept of mutation in a digital environment and showed that evolutionary processes previously only seen in nature can take place in the digital world. This eventually led to the “killer app” of self-replicating program research environments, “Avida”, developed by Charles Ofria at Michigan State University’s Digital Evolution Lab in 2000. Below is an animation showing successive generations of Avida organisms (Avidians) taking over the population as a sample evolution progresses:
At the 2010 Artificial Life XII conference in Odense, Denmark, the MSU team presented a paper describing some of their most recent work, including digital creatures that evolved the ability to follow paths along a grid. The environment was strewn with clues, signposts indicating which way the path would go. After tens of thousands of generations of evolution, the Avidians evolved reflex actions which successfully interpreted the signs as either “turn left” or “turn right”, giving them a survival advantage.
A program with just reflex actions can do quite a lot in a complex environment. What about using “volatile memory”, not just knee-jerk responses to the environment, but ones that depend on context? To encourage the evolution of volatile memory, the researchers put sign posts on the grid that symbolized “repeat last action”. The MSU team showed the Avidians were indeed able to take advantage of this information by evolving the ability to remember their last action.
The ability to remember and recall a single variable in the environment appears trivial, especially for a computer program, but the significance of this research is that no one programmed this behavior. The code which navigates the path and uses volatile memory to its advantage bubbled up from the raw evolutionary stew acting against a carefully crafted artificial environment that allowed such evolutionary pressure to exist.
There are many interesting questions here: Under what circumstances does evolutionary pressure tend to favor the development of micro brain structures? How can we configure artificial environments to evolve more complex bottom-up brains? How does the evolution of such structures manifest in nature?
Avida is a robust open-ended research tool and it is likely we will see many more groundbreaking projects coming from this platform for some time.
More:
The Replicators
In 1970, noting the extreme cost of space exploration, the physicist Freeman Dyson proposed a wild idea: send a machine into space that is capable of building copies of itself from materials it finds. This would provide an unlimited production and exploration capacity for a finite cost.
Although just a thought experiment, Dyson’s idea is not as crazy as it sounds. In the early 1980s, NASA funded a series of investigations into cheap space colonization which involved building self-replicating factories on the moon. It’s theoretically possible, but robot factories building more robot factories poses a huge maintenance problem. After all, you’d need an army of repair robots to fix things when they break down. And, who repairs the repair robots?
Eric Drexler, a proponent of nanotechnology, describes a more elegant solution. He envisions tiny, molecular “assemblers” that can build copies of themselves and other items of greater complexity — a bottom-up version of the self-replicating factory idea. He also notes that such technology, if not tamed properly, could replicate out of control consuming all the resources on the planet resulting in the so called Grey Goo Scenario.
 |
| Copyright Shane Willis |
Thought experiments aside, some researchers have succeeded in building primitive, yet practical self-replicating machines. Adrian Bowyer from the University of Bath developed a rapid prototyping machine called RepRap that can make most of the parts necessary to build… another RepRap machine.
Bowyer’s RepRap project is now replicating “in the wild”. On November 30, 2008, the first user outside the lab used one of the machines to produce and sell a set of RepRap parts to someone else. Being a prototyping machine, RepRap is not limited to copying itself. It has been used to create ordinary objects including a coathook, a pair of sandals, and a fly swatter. The potential for such a machine is vast and is fortunately not likely to turn the world into goo anytime soon.
More:
