Differential game theory for versatile physical human-robot interaction
- Submitting institution
-
University of Sussex
- Unit of assessment
- 12 - Engineering
- Output identifier
- 421198_81419
- Type
- D - Journal article
- DOI
-
10.1038/s42256-018-0010-3
- Title of journal
- Nature Machine Intelligence
- Article number
- -
- First page
- 36
- Volume
- 1
- Issue
- -
- ISSN
- 2522-5839
- Open access status
- Compliant
- Month of publication
- January
- Year of publication
- 2019
- URL
-
http://dx.doi.org/10.1038/s42256-018-0010-3
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
-
4
- Research group(s)
-
-
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This paper developed a general game theory framework for human-robot interaction, which was reported by 16 news outlets within 3 weeks after its publication. A proposal to harness impacts of this work was supported by an EPSRC New Investigators Award, which is carried out in collaboration with the rehabilitation robot companies Artecares (Dr Asif HUSSAIN, ahussain@articares.com) and Gripable (Dr Michael Mace, mike@gripable.co).
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -
