Abstract
This paper develops a distributed algorithm for decision/awareness propagation in mobile-agent networks. A time-dependent proximity network topology is adopted to represent a mobile-agent scenario. The agent-interaction policy formulated here is inspired from the recently developed language-measure theory. Analytical results related to convergence of statistical moments of agent states are derived and then validated by numerical simulation. The results show that a single (user-defined) parameter in the agent interaction policy can be identified to control the trade-off between Propagation Radius (i.e. how far a decision spreads from its source) and Localisation Gradient (i.e. the extent to which the spatial variations may affect localisation of the source) as well as the temporal convergence properties.
⋆An earlier version of the paper reporting preliminary results has been presented at the 2012 American Control Conference, Montreal, Canada.
Acknowledgements
This work has been supported in part by the Army Research Laboratory (ARL) and the Army Research Office (ARO) under Grant No. W911NF-07-1-0376, by the Office of Naval Research (ONR) under Grant No. N00014-09-1-0688 and by NASA under Cooperative Agreement No. NNX07AK49A. Any opinions, findings and conclusions or recommendations expressed in this publication are those of the authors and do not necessarily reflect the views of the sponsoring agencies.
Notes
⋆An earlier version of the paper reporting preliminary results has been presented at the 2012 American Control Conference, Montreal, Canada.