Abstract
Using teams of autonomous, heterogeneous robots to operate in dangerous environments means increased cost-effectiveness and the ability to spread skills among team members. The high risk of loss in these domains is a challenge to team management. Teams must be able to recruit the help of other robots in the environment, while balancing searching with performing immediately useful work. This paper describes additions to a framework for dynamic team management in dangerous domains in order to support various levels of active search for useful agents while balancing useful work in the domain.
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Nagy, G., Anderson, J. (2016). Active Recruitment Mechanisms for Heterogeneous Robot Teams in Dangerous Environments. In: Khoury, R., Drummond, C. (eds) Advances in Artificial Intelligence. Canadian AI 2016. Lecture Notes in Computer Science(), vol 9673. Springer, Cham. https://doi.org/10.1007/978-3-319-34111-8_34
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DOI: https://doi.org/10.1007/978-3-319-34111-8_34
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