Robots Evolve And Learn How to Lie

robot boyI was completely charmed by a report in the online science magazine Discover this week (h/t Slashdot):

Robots can evolve to communicate with each other, to help, and even to deceive each other, according to Dario Floreano of the Laboratory of Intelligent Systems at the Swiss Federal Institute of Technology. Floreano and his colleagues outfitted robots with light sensors, rings of blue light, and wheels and placed them in habitats furnished with glowing “food sources” and patches of “poison” that recharged or drained their batteries. Their neural circuitry was programmed with just 30 “genes,” elements of software code that determined how much they sensed light and how they responded when they did.

… To create the next generation of robots, Floreano recombined the genes of those that proved fittest—those that had managed to get the biggest charge out of the food source. The resulting code … was downloaded into the robots to make … offspring… By the 50th generation, the robots had learned to communicate… The fourth colony sometimes evolved “cheater” robots instead, which would light up to tell the others that the poison was food, while they themselves rolled over to the food source and chowed down without emitting so much as a blink.

The research of Floreano and colleagues is reported in the March 2007 issue of Current Biology. The researchers created four conditions for their experiments, varying the relatedness of the robots (how similar their ‘genes’ and programming were) and whether selection was on an individual level or colony level: “In the individual-level selection regime, the genomes of the 20% robots with the highest individual performance … were selected to form the next generation, whereas in the colony-level selection regime, we randomly selected all robots… from the 20% most efficient colonies” (p.514).

‘Deceptive’ communication only evolved when the robots were not closely ‘related’ to each other and selection was on an individual rather than a colony level. In this condition, “an analysis of individual behaviors revealed that … robots tended to emit blue light when far away from the food.” Despite this, and “contrary to what one would expect, the robots still tended to be attracted rather than repelled by blue light… ” (p.517).

The authors suggest that this is because, at least in early stages of evolution, more blue light = more robots, and robots tended to congregate around ‘food’. So, “the greater level of blue light emission associated with the greater density of robots near food provided a useful cue about food location”.

They go on to explain that “emission of light far from the food would then have evolved as a deceptive strategy for decreasing competition near the food. Consistent with this view, the tendency of robots to be attracted by blue light significantly decreased during the last 200 generations” (p.517).

There was a cost, however. This experimental condition (low-relatedness robots and individual-level selection) was the only condition…

… where the possibility to communicate did not translate into a higher foraging efficiency …In this case, the ability to signal resulted in a deceptive signaling strategy associated with a significant decrease in colony performance compared to the situation where robots could not emit blue light (p.517).

In other words, lying about where the food is might be good for the individual, but it doesn’t help the colony very much.

Reference:

Photo credit: baboon™, Creative Commons License

Abstract below the fold.

Information transfer plays a central role in the biology of most organisms, particularly social species [1] and [2]. Although the neurophysiological processes by which signals are produced, conducted, perceived, and interpreted are well understood, the conditions conducive to the evolution of communication and the paths by which reliable systems of communication become established remain largely unknown. This is a particularly challenging problem because efficient communication requires tight coevolution between the signal emitted and the response elicited [3]. We conducted repeated trials of experimental evolution with robots that could produce visual signals to provide information on food location. We found that communication readily evolves when colonies consist of genetically similar individuals and when selection acts at the colony level. We identified several distinct communication systems that differed in their efficiency. Once a given system of communication was well established, it constrained the evolution of more efficient communication systems. Under individual selection, the ability to produce visual signals resulted in the evolution of deceptive communication strategies in colonies of unrelated robots and a concomitant decrease in colony performance. This study generates predictions about the evolutionary conditions conducive to the emergence of communication and provides guidelines for designing artificial evolutionary systems displaying spontaneous communication.

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