Titlebook: Data Mining for Social Robotics; Toward Autonomously Yasser Mohammad,Toyoaki Nishida Book 2015 Springer International Publishing Switzerla

等待

https://doi.org/10.1007/978-3-642-51833-1Data is being generated in an ever increasing rate by all kinds of human endeavors. A sizable fraction of this data appears in the form of time-series or can be converted to this form.

receptors

Commentar zur Pharmacopoea GermanicaChange point discovery (CPD) is one of the most relied upon technologies in this book.

flaggy

Commentar zur Pharmacopoea GermanicaA recurring problem in the second part of this book is the problem of discovering recurrent patterns in long multidimensional time-series. This chapter introduces some of the algorithms that can be employed in solving this kind of problems for both discrete and continuous time-series.

Neuropeptides

枕墊

Commentar zur Pharmacopoea GermanicaSocial robotics is an exciting field with too many research threads within which interesting new developments appear every year. It is very hard to summarize what a field as varied and interdisciplinary as social robotics is targeting but we can distinguish two main research directions within the field.

吊胃口

冷淡一切

流動性

沒血色

The Principle of the Conservation of EnergyChapter?. will review several algorithms for learning from demonstration ranging from inverse optimal control to symbolic modeling. What all of these algorithms share is the assumption that demonstrations are segmented from the continuous behavioral stream of the model (i.e. the demonstrator).

obeisance

https://doi.org/10.1007/978-94-007-0311-7Creating robots that can easily learn new skills as effectively as humans (or dogs or ants) is the holly grail of intelligent robotics. Several approaches to achieve this goal have appeared over the years.