Name: Data Mining for Social Robotics: Toward Autonomously Social Robots (en Inglés)
Price: 2523.51 MXN
Availability: InStock
Author: Mohammad, Yasser ; Nishida, Toyoaki
ISBN: 9783319252308

Envío gratis

portada Data Mining for Social Robotics: Toward Autonomously Social Robots (en Inglés)

Formato

Libro Físico

Autor

Toyoaki Nishida

Yasser Mohammad

Editorial

Springer

Idioma

Inglés

N° páginas

328

Encuadernación

Tapa Dura

Dimensiones

23.4 x 15.6 x 2.1 cm

Peso

0.65 kg.

ISBN13

9783319252308

Categorías

Data mining: minería de datos
Inteligencia artificial

Data Mining for Social Robotics: Toward Autonomously Social Robots (en Inglés)

Toyoaki Nishida (Autor) · Yasser Mohammad (Autor) · Springer · Tapa Dura

Libro Nuevo

$ 2,523.51

$ 4,205.85

Ahorras: $ 1,682.34

40% descuento

Envío normal

Origen: Estados Unidos (Costos de importación incluídos en el precio)

Se enviará desde nuestra bodega entre el Lunes 29 de Julio y el Viernes 09 de Agosto.

Lo recibirás en cualquier lugar de México entre 1 y 3 días hábiles luego del envío.

Reseña del libro "Data Mining for Social Robotics: Toward Autonomously Social Robots (en Inglés)"

This book explores an approach to social robotics based solely on autonomous unsupervised techniques and positions it within a structured exposition of related research in psychology, neuroscience, HRI, and data mining. The authors present an autonomous and developmental approach that allows the robot to learn interactive behavior by imitating humans using algorithms from time-series analysis and machine learning. The first part provides a comprehensive and structured introduction to time-series analysis, change point discovery, motif discovery and causality analysis focusing on possible applicability to HRI problems. Detailed explanations of all the algorithms involved are provided with open-source implementations in MATLAB enabling the reader to experiment with them. Imitation and simulation are the key technologies used to attain social behavior autonomously in the proposed approach. Part two gives the reader a wide overview of research in these areas in psychology, and ethology. Based on this background, the authors discuss approaches to endow robots with the ability to autonomously learn how to be social. Data Mining for Social Robots will be essential reading for graduate students and practitioners interested in social and developmental robotics.