Task reallocation in a multi-robot organization is a process that distributes a decomposed global task to individual robots. This process must be distributed and dynamic because it relies on critical information that can only be obtained during mission execution. This paper presents a representation for this challenging problem and proposes an algorithm that allows member robots to trade tasks and responsibilities autonomously. Preliminary results show that such an algorithm can indeed improve the efficiency of organizational performance and construct a locally optimal (hill climbing) task allocation during mission execution.