Dynamic Model for Social Coalition Formation Based on Expertise, Temporal Reputation and Time Commitment

Abstract

Existing approaches to coalition formation are generally gross simplifications of real problems of resource allocation where experience, reputation, and time optimization should be considered, although they are not usually studied together. To overcome this issue, this study proposes a dynamic and distributed social coalition formation model, that reproduces real-world environments where interactions are ruled by an underlying network that adapts itself based on the best updated reputation of local neighbors, in order to bring together individuals better suited for efficient cooperation. In this environment, agents possessing different levels of expertise must be organized to provide the most advantageous partnerships for the purpose of solving tasks, and an execution order of task's subtasks is defined to favor the use and release of agents' resources. To achieve this objective, we based our proposal on a coalitional skill game (CSG) approach, which organizes the use of resources by time commitment, and calculates and exploits the temporal reputation of heterogeneous agents to improve the utility of coalitions. Our experiments with different initial social networks allowed us to evaluate the effectiveness of this proposal and provided elements to exploit the advantages of an optimized social structure in a connected world.