Paper Info
Title
Robot-Oriented Generative Learning Objects: An Agent-Based Vision.
Abstract
The paper presents a juxtaposing of the robot-oriented generative objects (GLOs) with software (SW) agents and identifies the capabilities to introduce more intelligence to the educational environment based on those GLOs. The main contribution of the paper is the agent-based architecture of the system and its partial implementation, enabling to solve the prescribed tasks more efficiently (with a less user's intervention and a higher robot's accuracy). Also the case study and some experimental results are described.
Year
DOI
Venue
2016
10.1007/978-3-319-39883-9_20
AGENT AND MULTI-AGENT SYSTEMS: TECHNOLOGY AND APPLICATIONS, KES-AMSTA 2016
Keywords
Field
DocType
Generative learning objects,Software agents,Educational robots
Architecture,Computer science,Software agent,Human–computer interaction,Software,Artificial intelligence,Generative grammar,Educational robotics,Robot,Machine learning,Generative model
Conference
Volume
ISSN
Citations 
58
2190-3018
0
PageRank 
References 
Authors
0.34
0
4
Name
Order
Citations
PageRank
Vytautas Stuikys110217.07
Renata Burbaite2123.98
Vida Drasute301.01
Kristina Bespalova442.43