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Monday, February 01, 2010

If you can't get Mohammed to the mountain...

Critics of the theory of evolution sometimes argue that evolution is pseudoscientific because it is allegedly immune to falsification. Specifically, because evolution took place over long spans of geologic time the claim is that we can't reproduce evolution in a laboratory and, as such, the validity of evolutionary theory cannot be determined. This is, of course, incorrect. There's plenty of evidence all around us supporting the theory of evolution, much of which is discussed on Richard Dawkin's book The Greatest Show on Earth.* Perhaps more importantly there are experiments- like Richard Lenski's work with bacteria- that can and do catch evolution in the act. Yet, even with all this, the argument is sometimes advanced that evolution can't explain truly complex things, like the brain and behaviors.

And this is where the robots come in. Recently, scientists have been exploring the issue of evolution by using robots as simple analogs. And the results are superb:

Ever since Cicero's De Natura Deorum ii.34., humans have been intrigued by the origin and mechanisms underlying complexity in nature. Darwin suggested that adaptation and complexity could evolve by natural selection acting successively on numerous small, heritable modifications. But is this enough? Here, we describe selected studies of experimental evolution with robots to illustrate how the process of natural selection can lead to the evolution of complex traits such as adaptive behaviours. Just a few hundred generations of selection are sufficient to allow robots to evolve collision-free movement, homing, sophisticated predator versus prey strategies, coadaptation of brains and bodies, cooperation, and even altruism. In all cases this occurred via selection in robots controlled by a simple neural network, which mutated randomly.

Genes do not specify behaviours directly but rather encode molecular products that lead to the development of brains and bodies through which behaviour is expressed. An important task is therefore to understand how adaptive behaviours can evolve by the mere process of natural selection acting on genes that do not directly code for behaviours. A spectacular demonstration of the power of natural selection comes from experiments in the field of evolutionary robotics, where scientists have conducted experimental evolution with robots. Evolutionary robotics has also been advocated as a method to automatically generate control systems that are comparatively simpler or more efficient than those engineered with other design methods because the space of solutions explored by evolution can be larger and less constrained than that explored by conventional engineering methods. In this essay we will examine key experiments that illustrate how, for example, robots whose genes are translated into simple neural networks can evolve the ability to navigate, escape predators, coadapt brains and body morphologies, and cooperate. We present mostly—but not only—experimental results performed in our laboratory, which satisfy the following criteria. First, the experiments were at least partly carried out with real robots, allowing us to present a video showing the behaviours of the evolved robots. Second, the robot's neural networks had a simple architecture with no synaptic plasticity, no ontogenetic development, and no detailed modelling of ion channels and spike transmission. Third, the genomes were directly mapped into the neural network (i.e., no gene-to-gene interaction, time-dependent dynamics, or ontogenetic plasticity). By limiting our analysis to these studies we are able to highlight the strength of the process of Darwinian selection in comparable simple systems exposed to different environmental conditions. There have been numerous other studies of experimental evolution performed with computer simulations of behavioural systems. Reviews of these studies can be found in. Furthermore, artificial evolution has also been applied to disembodied digital organisms living in computer ecosystems, such as Tierra and Avida, to address questions related to gene interactions, evolution of complexity, and mutation rates.

...

Conclusions

These examples of experimental evolution with robots verify the power of evolution by mutation, recombination, and natural selection. In all cases, robots initially exhibited completely uncoordinated behaviour because their genomes had random values. However, a few hundreds of generations of random mutations and selective reproduction were sufficient to promote the evolution of efficient behaviours in a wide range of environmental conditions. The ability of robots to orientate, escape predators, and even cooperate is particularly remarkable given that they had deliberately simple genotypes directly mapped into the connection weights of neural networks comprising only a few dozen neurons.


To make that even simpler: fast adaptation to conditions was observed for robots using simple neural networks and very low-level mutations (i.e. mutations at a level below full code). We've reached the point where we're not just finding evidence for evolution in biology, in geology, and in genetics- but in laboratory experiments as well. And I'm grateful for this, really. For years we've been trying to get the creationist Mohammed to visit the mountain of evidence for evolution with no success. Now, thanks to innovative experiments, maybe we can plant the mountain right down in their back yards.



* An interesting read, though not something that is going to sway a committed anti-evolutionist.

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