Aggregation, whether it be in natural or artificial systems, provides numerous benefits to both the individual and the group. However, aggregation has costs and frequently involves inter-individual conflict. Although conflicts in natural systems is understood to be at times beneficial, as well as detrimental, conflict in artificial systems, such as a team of robots, is frequently viewed as inhibiting consensus and, therefore, success. This is particularly the case in large-scale aggregations where ensuring consensus is especially challenging. In response, mechanisms are often integrated into the group's control systems to minimize, or even eliminate, conflicts of interest. As a result, the potential benefits of losing consensus, such as increased diversity and reduced consensus costs, are not available. Using a biologically-based collective movement model, we demonstrate that not enforcing consensus and allowing conflict to evolve as agents make decisions results in a system in which agents meet their own needs, thus minimizing consensus costs, while still maintaining group cohesion when possible. Simulations predict that conflict balances consensus costs with individual preferences such that both individual and group goals are met.
It is commonly observed that aggregation in nature provides significant benefits to the group members. However, to reach a consensus individual preferences are frequently lost. Conflict is generally avoided because of the negative influence it could have on the success of collective movements. However, it could be used to balance consensus costs with individual preferences. Using a biologically-based collective movement model, this work investigates the possibility of conflict in a group movement allowing for differing individual goals to be accomplished, while still maintaining group cohesion much of the time. Individuals focus on their own needs, which may include the protection of being a part of a group or the desire to move away from the group and towards its preferred destination. Results show that by allowing conflict in group decision-making, consensus costs were balanced with individual preferences in such a way that group level success still occurred, while significantly improving the success of differing goals.
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