Cantitate/Preț
Produs
Total produse
Vezi coșul
Evolutionary Robotics de Philip Husbands

Evolutionary Robotics

Editat de Philip Husbands, Jean-Arcady Meyer
en Limba Engleză Paperback – 12 aug 1998
This book constitutes the thorougly refereed and revised post-workshop proceedings of the First European Workshop on Evolutionary Robotics, EvoRobot '98, held in Paris, France in April 1998.
The 15 revised full papers presented outline the state of the art in this new interdisciplinary area of research and development. The introductory paper gives a survey of the use of evolutionary computing techniques for the automatic design of adaptive robots.
Citește tot Restrânge

Preț: 37409 lei

Puncte Express: 561

Carte tipărită la comandă

Livrare economică 08-22 iulie

Livrare prin curier în România Termenul estimat este afișat lângă disponibilitate.
Transport gratuit de la 40000 lei Plată online sau ramburs, în funcție de opțiunile comenzii.
Retur gratuit în 14 zile Comandă securizată și suport în română.
 Adaugă în coș

Wish list
Gift list
Am citit!
Adaugă în listă

Specificații

ISBN-13: 9783540649571
ISBN-10: 3540649573
Pagini: 264
Ilustrații: VIII, 252 p.
Dimensiuni: 155 x 235 x 15 mm
Greutate: 0.41 kg
Ediția:1998
Editura: Springer
Locul publicării:Berlin, Heidelberg, Germany

Public țintă

Research

Cuprins

Evolutionary robotics: A survey of applications and problems.- How co-evolution can enhance the adaptive power of artificial evolution: Implications for evolutionary robotics.- Running across the reality gap: Octopod locomotion evolved in a minimal simulation.- Detour behavior in evolving robots: Are internal representations necessary?.- Evolving robot behaviours with diffusing gas networks.- Explaining the evolved: Homunculi, modules, and internal representation.- Some problems (and a few solutions) for open-ended evolutionary robotics.- Noise and the pursuit of complexity: A study in evolutionary robotics.- Hardware solutions for evolutionary robotics.- Blurred vision: Simulation-reality transfer of a visually guided robot.- Learning to move a robot with random morphology.- Learning behaviors for environmental modeling by genetic algorithm.- Evolving and breeding robots.- Off-line model-free and on-line model-based evolution for tracking navigation using evolvable hardware.- Incremental evolution of neural controllers for robust obstacle-avoidance in Khepera.