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Evolution of Adaptive Behaviour in Robots by Means of Darwinian Selection

Dario Floreano1*, Laurent Keller2*

1 Laboratory of Intelligent Systems, Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland, 2 Department of Ecology and Evolution, University of Lausanne, Biophore, Lausanne, Switzerland

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 [1],[2], 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 [3]. 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 [4][6]. Furthermore, artificial evolution has also been applied to disembodied digital organisms living in computer ecosystems, such as Tierra [7] and Avida [8], to address questions related to gene interactions [9], evolution of complexity [10], and mutation

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Februar 8, 2010 Posted by | Presse | , | 3 Kommentare

Did Dark Matter Destroy Universe 1.0?

No galaxies have been seen before at such early epochs as that seen in this deepest images of the universe ever taken in near-infrared light by NASA’s Hubble Space Telescope (see video below). The faintest and reddest objects in the image are galaxies that correspond to „look-back times“ of approximately 12.9 billion years to 13.1 billion years ago.

A longstanding enigma is that it still appears that these early galaxies did not emit enough radiation to „reionise“ the early Universe by stripping electrons from the neutral hydrogen that cooled after the Big Bang. This „reionisation“ event occurred between about 400 million and 900 million years after the Big Bang, but astronomers still don’t know which light sources caused it to happen. These newly discovered galaxies date from this important epoch in the evolution of the Universe.

It took about the first billion years to completely ionize the Universe; before that, the Universe was opaque to light, with neutral atoms acting like dust. As the Universe reionizes, it becomes easier to see the light from whatever objects are behind it. The youngest object ever discovered in the universe, Gamma Ray Burst GRB 090423, born when the Universe was under 0.7 billion years old. This thing is so far away that no visible light actually got out; we can only see the X-rays from it

These early Hubble galaxies are much smaller than the Milky Way and other spiral galaxies and have populations of stars that are intrinsically very blue. This may indicate the galaxies are so primordial that they are deficient in heavier elements, and as a result, are quite free of the dust that reddens light through scattering.

Ross McLure of the Institute for Astronomy at Edinburgh University and his team detected 29 galaxy candidates, of which twelve lie beyond redshift 6.3 and four lie beyond redshift 7 (where the redshifts correspond to 890 million years and 780 million years after the Big Bang respectively). He notes that „the unique infrared sensitivity of Wide Field Camera 3 means that these are the best images yet for providing detailed information about the first galaxies as they formed in the early Universe“.

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Februar 8, 2010 Posted by | Presse | , | Hinterlasse einen Kommentar