1. Geoff Nagy and John Anderson. Active Team Management Strategies for Multi-robot Teams in Dangerous Environments. In Advances in Artificial Intelligence: 30th Canadian Conference on Artificial Intelligence, Edmonton, AB, pages 385-396, May 2017. Note: Best Paper Award. Abstract:

   Cost-effectiveness, management of risk, and simplicity of design are all arguments in favour of using heterogeneous multi-robot teams in dangerous domains. Robot losses are expected to occur and the loss of useful skills means that replacement robots - either released into the environment or previously lost and rediscovered - must be recruited for useful work. While teams of robots may eventually encounter replacements by chance, more active search strategies can be used to locate them more quickly, either to complete a single task or join a team. These searches, however, must be balanced with existing tasks so that the team can still perform useful work in the domain. This paper describes additions that we have made to an existing framework for managing dynamic teams in dangerous domains in order to support this goal.

   
   

   @inproceedings{NagyAndersonAI17,
   author = {Geoff Nagy and John Anderson},
   title = {Active Team Management Strategies for Multi-robot Teams in Dangerous Environments},
   booktitle = {Advances in Artificial Intelligence: 30th Canadian Conference on Artificial Intelligence},
   year = {2017},
   month = {May},
   pages = {385--396},
   doi = {10.1007/978-3-319-57351-9 43},
   note = {Best Paper Award},
   address = {Edmonton, AB},
   pdf = {http://aalab.cs.umanitoba.ca/%7eandersj/Publications/pdf/NagyAndersonAI17.pdf},
   abstract = {Cost-effectiveness, management of risk, and simplicity of design are all arguments in favour of using heterogeneous multi-robot teams in dangerous domains. Robot losses are expected to occur and the loss of useful skills means that replacement robots - either released into the environment or previously lost and rediscovered - must be recruited for useful work. While teams of robots may eventually encounter replacements by chance, more active search strategies can be used to locate them more quickly, either to complete a single task or join a team. These searches, however, must be balanced with existing tasks so that the team can still perform useful work in the domain. This paper describes additions that we have made to an existing framework for managing dynamic teams in dangerous domains in order to support this goal.} 
   }
   

1. Kyle J. Morris, Vlad Samonin, John E. Anderson, Meng Cheng Lau, and Jacky Baltes. Robot Magic: A Robust Interactive Entertainment Robot. Note: 1st Place Poster, Applied Science, Undergraduate Research Poster Competition, University of Manitoba, October 2017.
   

   @unpublished{17PosterComp
   }, author = {Kyle J. Morris and Vlad Samonin and John E. Anderson and Meng Cheng Lau and Jacky Baltes
   }, title = {Robot Magic: A Robust Interactive Entertainment Robot
   }, year = {2017
   }, month = {October
   }, pdf = {http://aalab.cs.umanitoba.ca/%7eandersj/Publications/pdf/RM17Poster.png
   }, note = {1st Place Poster,
   Applied Science,
   Undergraduate Research Poster Competition,
   University of Manitoba
   } }
   

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