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Coalition imbalance or lopsidedness is defined as the degree of unevenness of resource contributions made by individual members to the coalition. This characteristic is not considered in other coalition formation algorithms. A coalition where one or more agents have a predominant share of the capabilities may have the same utility as a coalition with evenly distributed capabilities.
Robots are typically unable to redistribute their resources. Therefore coalitions with one or more dominating members (resource contributors) tend to be heavily dependent on those members for task execution. These dominating members then become indispensable. Such coalitions should be avoided in order to improve fault tolerance in automation. Over reliance on dominating members can cause task execution to fail or considerably degrade.
If a Robot is not a dominating member (does not possess many sensors) then it is more likely that another robot with similar capabilities can replace this robot. The Balance Coefficient metric quantifies the coalition imbalance level. Simulation experiments were performed in the Player/Stage simulation environment to demonstrate the effect that the balance coefficient would have on fault tolerance of robot teams.
The algorithm was then transferred to actual robots in which the box-pushing task was used as a proof of concept experiment. The translation of the simulation experiments to real world robot experiments required a few adjustments to account for problems of slippage and mapping of capabilities to real numbers. However, the experiments successfully establish that the algorithm performs satisfactorily with real robots.
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