Special Issue "Intelligent Robots"
A special issue of Robotics (ISSN 2218-6581).
Deadline for manuscript submissions: closed (31 March 2013)
Prof. Dr. Genci Capi
Department of Electrical and Electronic Systems Engineering, Faculty of Engineering, University of Toyama Gofuku Campus, 3190 Gofuku, Toyama, 930-8555, Japan
Phone: +81 76 445 6745
Interests: evolutionary robotics; human-robot interaction; reinforcement learning; humanoid robots; service robots; intelligent robots
Future robots are expected to operate in unstructured and unpredicted environments. Therefore, the robots must adapt their policy as environment changes. Learning and evolution have been proved to give good results generating a good mapping of various sensory data to robot action. The goal of this special issue is to bring together recent works from a wide range of topics concerning application of learning and evolution in robotics.
The scope of the special issue includes but is not limited:
- Reinforcement learning
- Evolutionary robotics
- Sensorimotor learning
- Combining learning and evolution
- Hierarchical learning
- Biologically motivated neural controllers
- Imitation learning
- Learning and evolution in multi robotic systems
Prof. Dr. Genci Capi
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. Papers will be published continuously (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (N.B. Conference papers may only be submitted if the paper was not originally copyrighted and if it has been extended substantially and completely re-written). All manuscripts are refereed through a peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Robotics is an international peer-reviewed Open Access quarterly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. For the first couple of issues the Article Processing Charge (APC) will be waived for well-prepared manuscripts. English correction and/or formatting fees of 250 CHF (Swiss Francs) will be charged in certain cases for those articles accepted for publication that require extensive additional formatting and/or English corrections.
- reinforcement learning
- evolutionary robotics
- imitation learning
- hybrid learning
Editorial: Special Issue on Intelligent Robots
Robotics 2013, 2(3), 185-186; doi:10.3390/robotics2030185
Received: 1 August 2013; Accepted: 2 August 2013 / Published: 6 August 2013| Download PDF Full-text (59 KB) | View HTML Full-text | Download XML Full-text
Robotics 2013, 2(3), 165-184; doi:10.3390/robotics2030165
Received: 1 June 2013; in revised form: 15 July 2013 / Accepted: 16 July 2013 / Published: 24 July 2013| Download PDF Full-text (4806 KB)
Robotics 2013, 2(3), 149-164; doi:10.3390/robotics2030149
Received: 30 May 2013; in revised form: 25 June 2013 / Accepted: 27 June 2013 / Published: 10 July 2013| Download PDF Full-text (431 KB) | View HTML Full-text | Download XML Full-text
Robotics 2013, 2(3), 122-148; doi:10.3390/robotics2030122
Received: 4 June 2013; in revised form: 24 June 2013 / Accepted: 28 June 2013 / Published: 5 July 2013| Download PDF Full-text (1941 KB)
Robotics 2013, 2(2), 66-91; doi:10.3390/robotics2020066
Received: 1 April 2013; in revised form: 4 May 2013 / Accepted: 13 May 2013 / Published: 21 May 2013| Download PDF Full-text (635 KB)
Robotics 2013, 2(2), 54-65; doi:10.3390/robotics2020054
Received: 27 March 2013; in revised form: 16 April 2013 / Accepted: 19 April 2013 / Published: 29 April 2013| Download PDF Full-text (723 KB) | View HTML Full-text | Download XML Full-text
Last update: 5 October 2012