Communication in Natural and Artificial Organisms: Experiments in Evolutionary Robotics

2007 ◽  
pp. 189-205 ◽  
Author(s):  
Davide Marocco ◽  
Stefano Nolfi
Keyword(s):  
Evolutionary Robotics

scholarly journals Development of Multiple Behaviors in Evolving Robots

Robotics ◽  
2020 ◽  
Vol 10 (1) ◽  
pp. 1
Author(s):  
Victor Massagué Respall ◽  
Stefano Nolfi
Keyword(s):  
Evolutionary Algorithms ◽  
State Of The Art ◽  
Evolutionary Robotics ◽  
The Other ◽  
Evolutionary Strategies ◽  
Multiple Behaviors ◽  
Pareto Fronts ◽  
Expected Fitness

We investigate whether standard evolutionary robotics methods can be extended to support the evolution of multiple behaviors by forcing the retention of variations that are adaptive with respect to all required behaviors. This is realized by selecting the individuals located in the first Pareto fronts of the multidimensional fitness space in the case of a standard evolutionary algorithms and by computing and using multiple gradients of the expected fitness in the case of a modern evolutionary strategies that move the population in the direction of the gradient of the fitness. The results collected on two extended versions of state-of-the-art benchmarking problems indicate that the latter method permits to evolve robots capable of producing the required multiple behaviors in the majority of the replications and produces significantly better results than all the other methods considered.

scholarly journals How to promote generalisation in evolutionary robotics

2011 ◽  
Author(s):  
Tony Pinville ◽  
Sylvain Koos ◽  
Jean-Baptiste Mouret ◽  
Stéphane Doncieux
Keyword(s):  
Evolutionary Robotics

scholarly journals Coevolving Predator and Prey Robots: Do “Arms Races” Arise in Artificial Evolution?

1998 ◽  
Vol 4 (4) ◽  
pp. 311-335 ◽  
Author(s):  
Stefano Nolfi ◽  
Dario Floreano
Keyword(s):  
Evolutionary Robotics ◽  
Arms Race ◽  
Artificial Evolution ◽  
Arms Races ◽  
Wide Range ◽  
Evolutionary Arms Race ◽  
Adaptive Power ◽  
Competing Populations

Coevolution (i.e., the evolution of two or more competing populations with coupled fitness) has several features that may potentially enhance the power of adaptation of artificial evolution. In particular, as discussed by Dawkins and Krebs [3], competing populations may reciprocally drive one another to increasing levels of complexity by producing an evolutionary “arms race.” In this article we will investigate the role of coevolution in the context of evolutionary robotics. In particular, we will try to understand in what conditions coevolution can lead to “arms races.” Moreover, we will show that in some cases artificial coevolution has a higher adaptive power than simple evolution. Finally, by analyzing the dynamics of coevolved populations, we will show that in some circumstances well-adapted individuals would be better advised to adopt simple but easily modifiable strategies suited for the current competitor strategies rather than incorporate complex and general strategies that may be effective against a wide range of opposing counter-strategies.

Evolutionary robotics

2004 ◽  
Author(s):  
Philip Husbands ◽  
Inman Harvey ◽  
Nicholas Jakobi ◽  
Adrian Thompson ◽  
Dave Cliff
Keyword(s):  
Evolutionary Robotics

NERD Neurodynamics and Evolutionary Robotics Development Kit

2010 ◽  
pp. 121-132 ◽  
Author(s):  
Christian Rempis ◽  
Verena Thomas ◽  
Ferry Bachmann ◽  
Frank Pasemann
Keyword(s):  
Evolutionary Robotics
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