Using Robots to Understand the Evolution of Language

Friday, January 6, 2012


An experiment led at EPFL and UNIL (Université de Lausanne) by Steffen Wischmann, Dario Floreano and Laurent Keller showed that "simple" robots equipped with a neural controller and an artificial genome have been able to develop two different "languages" (signaling strategies). Though the simplest was the most efficient on its own, the robots using a more complex language outperformed the others when both popluations were in a competition.

The abstract from the published paper mentions that one of the key innovations during the evolution of life on earth has been the emergence of efficient communication systems, yet little is known about the causes and consequences of the great diversity within and between species.




The researchers conducted experimental evolution in 20 independently evolving populations of cooperatively foraging simulated robots, and found that historical contingency in the occurrence order of novel phenotypic traits resulted in the emergence of two distinct communication strategies. The more complex foraging strategy was less efficient than the simpler strategy. However, when the 20 populations were placed in competition with each other, the populations with the more complex strategy outperformed the populations with the less complex strategy.

These results demonstrate a tradeoff between communication efficiency and robustness and suggest that stochastic events have important effects on signal evolution and the outcome of competition between distinct populations.

Moreover, the experiment shows that robotics are an exponentially growing technology.  In this experiment, computation is used to examine factors that take thousands of years to develop in biological creatures.

http://www.pnas.org/content/early/2012/01/02/1104267109

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