En raison d'une grève chez bpost, des retards de livraison peuvent survenir. Besoin de quelque chose en urgence ? Optez pour un retrait en magasin ou rendez-vous dans une Librairie Club à proximité.

Retrait en 2 heures
Assortiment impressionnant
Paiement sécurisé
Toujours un magasin près de chez vous

Retrait en 2 heures
Assortiment impressionnant
Paiement sécurisé
Toujours un magasin près de chez vous

Magasins

Wishlist

Magasins

Wishlist

Chercher

Promotions

73,95 €

+ 147 points

Livraison sous 1 à 4 semaines

Passer une commande en un clic

Payer en toute sécurité

Livraison en Belgique: 3,99 €

Livraison en magasin gratuite

Description

Today, autonomous robots are used in a rather limited range of applications such as exploration of inaccessible locations, cleaning floors, mowing lawns etc. However, ongoing hardware improvements (and human fantasy) steadily reveal new robotic applications of significantly higher sophistication. For such applications, the crucial bottleneck in the engineering process tends to shift from physical boundaries to controller generation. As an attempt to automatize this process, Evolutionary Robotics has successfully been used to generate robotic controllers of various types. However, a major challenge of the field remains the evolution of truly complex behavior. Furthermore, automatically created controllers often lack analyzability which makes them useless for safety-critical applications. In this book, a simple controller model based on Finite State Machines is proposed which allows a straightforward analysis of evolved behaviors. To increase the model's evolvability, a procedure is introduced which, by adapting the genotype-phenotype mapping at runtime, efficiently traverses both the behavioral search space as well as (recursively) the search space of genotype-phenotype mappings. Furthermore, a data-driven mathematical framework is proposed which can be used to calculate the expected success of evolution in complex environments.