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and old. When the communication graph is connected or connected with high probabil-
ity, it is, however, more convenient to share the data. Furthermore, from the experiments
it is visible that the assignment algorithms of two groups of agents where both groups
are mobile and moving towards one another, converges more rapidly than the algorithm
[12] with only one moving group.
6
Conclusions
In this paper, we explored how social behaviors, such as compromise, selflessness or
selfishness, and negotiation influence the total group's assignment solution when the
agents' communication range is insufficient for connected communication graph. A de-
centralized implementation of the Bertsekas' auction algorithm was presented to solve a
Multi-Agent (robot) Target Assignment problem with two groups of mobile agents. We
examined the dynamics of the assignment solution in respect to the maximum distance
stepped by the agents between two consecutive time periods and the quantity of the
information exchanged within the communicating agents. When uncertainty in the en-
vironment is elevated due to possible unpredicted events, past information dependent on
time of observation, exchanged among agents, may be inaccurate and prove a distrac-
tion for agents. We proved through the simulations that in a dynamic environment with
mobile targets, with the communication range under the CTR, the selfish approaches in
information exchange result in better system's performance. In the future work we plan
to implement the presented algorithm on a collaborative scenario in the coordination of
ambulances in the medical emergency management and an antagonistic scenario for the
case of reunion of two military groups on an unknown enemy area.
Acknowledgements. This work was supported in part by the Spanish Ministry of Sci-
ence and Innovation through the projects ”AT” (Grant CONSOLIDER CSD2007-0022,
INGENIO 2010) and ”OVAMAH” (Grant TIN2009-13839-C03-02).
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