TR Editors' blog

Robots 'Evolve' the Ability to Deceive

An experiment shows how "deceptive" behavior can emerge from simple rules.

Kristina Grifantini 08/18/2009

  • 7 Comments
Courtesy of PNAS

Researchers at the Ecole Polytechnique Fédérale de Lausanne in Switzerland have found that robots equipped with artificial neural networks and programmed to find "food" eventually learned to conceal their visual signals from other robots to keep the food for themselves. The results are detailed in an upcoming PNAS study.

The team programmed small, wheeled robots with the goal of finding food: each robot received more points the longer it stayed close to "food" (signified by a light colored ring on the floor) and lost points when it was close to "poison" (a dark-colored ring). Each robot could also flash a blue light that other robots could detect with their cameras.

"Over the first few generations, robots quickly evolved to successfully locate the food, while emitting light randomly. This resulted in a high intensity of light near food, which provided social information allowing other robots to more rapidly find the food," write the authors.

The team "evolved" new generations of robots by copying and combining the artificial neural networksof the most successful robots. The scientists also added a few random changes to their code to mimic biological mutations.

Because space is limited around the food, the bots bumped and jostled each other after spotting the blue light. By the 50th generation, some eventually learned to not flash their blue light as much when they were near the food so as to not draw the attention of other robots, according to the researchers. After a few hundred generations, the majority of the robots never flashed light when they were near the food. The robots also evolved to become either highly attracted to, slightly attracted to, or repelled by the light.

Because robots were competing for food, they were quickly selected to conceal this information," the authors add.

The researchers suggest that the study may help scientists better understand the evolution of biological communication systems.

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ms

190 Comments

  • 910 Days Ago
  • 08/19/2009

cooperation?

I wonder what modifications could be made to those simple rules (and/or to the method by which the "genes" are recombined) to produce cooperation amongst robots of the same "species"?

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rpelkey

1 Comment

  • 909 Days Ago
  • 08/20/2009

Re: cooperation?

it seems to me that creating cooperation wouldn't need a changing of the rules or the evolutionary process, but a changing of the game. in this game there was no preset strategy of competition, it just so happens that that strategy yielded the most points, and is therefore the one that evolved naturally. create a game where the payoff might be greater through cooperation, and i'm betting the bots find the strategy on their own.

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ketanco

3 Comments

  • 909 Days Ago
  • 08/20/2009

assigning points or costs will have so many applications

The fact that the algorithm enables robots to develop certain behaviours is very useful in many cases. “Earning points”, “assigning costs” etc… are actually very commonly used in many different applications and this is nothing new. The only thing changing is, as the visual processing, motion mechanisms, hardware etc… evolve, the same principle enables robots to perform different tasks. Playing chess for instance, which has since long been achieved by AI, has the same principle. It assigns costs to moves and then determines the best move. Another example looks very different, and much more complicated, but it is still the same basic principle. Recently the scientists at carnegie mellon university enabled the famous robot ASIMO to walk through moving set of obstacles. Again, the robot uses cost assignment / earning points principle, and based on the assigned costs, it determines the best route for that moment and moves accordignly. To see that article visit: www.roboticmagazine.com/androids/019-improved-navigation-for-androids.html . This principle will have much more practical applications, as the robotic hardware and software capabilities evolve. Even for humans it is the underlying principle for many different ways of thinking. In this example the robot knows nothing about “lying” to each other, or in chess the AI knows nothing about a chess game but they are simply trying to earn more points, which is something machines are very good at doing. This principle will have so many applications that I believe soon it will enable humanoid/android robots to bring the tea tray from the kitchen on our command.

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hosting

1 Comment

  • 909 Days Ago
  • 08/20/2009

Re: assigning points or costs will have so many applications

Waiting more news from carnegie mellon university. I have a friend from there and peoples from there is sometype magicians :)

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johnnyschad

1 Comment

  • 908 Days Ago
  • 08/21/2009

What about Bee's?

It would be at least as interesting to compare the behavior of these robots to that of bees, wasps, termites or ants that have such a sophisticated communication system and protocol.  It is fascinating that the robots didn't pick a more collective model.

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Monsterboy

92 Comments

  • 907 Days Ago
  • 08/22/2009

How competition?

Read the article a couple of times and didn't see what mechanism was used to create competition: were the points gained from being by the light ring divided by the number of robots there, or was it "used up" sooner, or what? Just curious.

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Rant93

1 Comment

  • 906 Days Ago
  • 08/23/2009

Re: How competition?

>The team "evolved" new generations of robots by copying and combining the artificial neural networks of the most successful robots.

More points = more successful = more likely to get used to breed the next generation.

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