Leveraging Social Networks to Motivate Humans to Train Agents

Authors
Publication date 2014
Host editors
  • A. Lomuscio
  • P. Scerri
  • A. Bazzan
  • M. Huhns
Book title AAMAS '14: proceedings of the 2014 International Conference on Autonomous Agents & Multiagent Systems
Book subtitle May 5-9, 2014, Paris, France
ISBN
  • 9781450327381
Event AAMAS '14
Pages (from-to) 1571-1572
Publisher Richland, SC: International Foundation for Autonomous Agents and Multiagent Systems
Organisations
  • Faculty of Science (FNWI) - Informatics Institute (IVI)
Abstract
Learning from rewards generated by a human trainer observing the agent in action has been demonstrated to be an effective method for humans to teach an agent to perform challenging tasks. However, how to make the agent learn most efficiently from these kinds of human reward is still under-addressed. In this paper, we investigate the effect of providing social-network-based feedback intended to engender trainer competitiveness, focusing on its impact on the trainer's behavior. The results of our user study with 85 subjects show that the agent's social feedback can induce the trainer to train longer and give more feedback. Furthermore, the agent's performance was much better when social-competitive feedback was provided. The results also show that making the feedback active further increases the amount of time trainers spend training but does not further improve agent performance.
Document type Conference contribution
Note Extended abstract
Language English
Published at http://dl.acm.org/citation.cfm?id=2616067 http://www.aamas-conference.org/Proceedings/aamas2014/aamas/p1571.pdf
Permalink to this page
Back